Accumulation, contamination, health and ecological risk assessment of heavy metals in landfill soil: Case study of Shiraz city in the Middle East

Accumulation, contamination, health and ecological risk assessment of heavy metals in landfill soil: Case study of Shiraz city in the Middle East | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Accumulation, contamination, health and ecological risk assessment of heavy metals in landfill soil: Case study of Shiraz city in the Middle East Ali Ghandeharizadeh, mansooreh Dehghani, Abolfazl Azhdarpoor, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4320875/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 Population concentration in metropolitan areas generates and disposes of substantial quantities of waste with varying compositions. Transporting this waste to landfills produces leachate, which causes harmful heavy metal pollution. In this study, seven soil sampling stations were established at Shiraz Engineering Landfill, with five additional stations near residential areas. Sampling occurred during low and high rainfall seasons. The Aqua Regia method determined heavy metal concentrations. The share of these heavy metals in landfill soil was as follows: 42.20% for Ni, 29.06% for Cr, 17.42% for Cu, 7.24% for Co, 3.95% for As, and only 0.13% for Cd metal. The average pollution load index in the analyzed soils was 2.58 and it showed the High level of pollution of these soils. The ecological risk index for residential areas and most landfill locations (excluding the recycling plant) fell within the low pollution category. The results of the non-carcinogenic risk assessment indicated that the hazard index (HI) for all heavy metals in the soil samples of the study area was 0.3933 for children and 0.0854 for adults. These values suggest that workers at the landfill site and children and adults residing near the site are not exposed to short-term risks associated with heavy metals. The chronic and long-term carcinogenic risk (TCR) for the studied heavy metals in the landfill soil exceeded the threshold of 1×10 -4 for both adults and children, indicating an unacceptable and dangerous risk to human health. For soil samples from residential areas, the TCR value for children was 1.30×10 -4 , indicating the risk of carcinogenesis specifically for children. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Solid earth sciences Health sciences/Health occupations Ecological and health risk assessment soil landfill Shiraz Solid waste Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights There was an unacceptable health risk for workers at landfill. For landfill workers, there was a danger of cancer. children who work and even other children who are near landfills are susceptible to cancer. The soil in the vicinity of the recycling plant has the highest concentration of heavy metals. 1. Introduction Heavy metals are considered environmental pollutants, consisting of metals and metalloids with a density > 5 g/cm 3 . When heavy metals seep into the soil, they pose a major threat to human health, other animals, and the biosphere. These heavy metals can enter the human body through a variety of pathways, including dermal contact, absorption, inhalation, soil ingestion, and consumption of contaminated food ( 1 , 2 ). Soil, which is composed of minerals, water, and air, is vital to our environment. In the world of today, soil pollution has equaled the importance of pollution from the air and water ( 3 ). One of the chronic consequences of heavy metal toxicity in soil is its effects on the human nervous system ( 4 ). Specific heavy metals have been associated with various health concerns. For instance, nickel (Ni) exposure can lead to lung and nasal cavity cancers, allergies, rhinitis, and sinusitis ( 5 ). Chromium (Cr), another heavy metal, has been linked to kidney disorders, skin sensitivity, and lung cancer ( 6 ). Copper (Cu) toxicity, resulting from an elevated copper concentration in the body, can cause chronic copper poisoning, respiratory tract and throat irritation, vomiting, diarrhea, delayed fetal growth, and an increased risk of Alzheimer's disease ( 7 ). Arsenic (As), a well-known heavy metal, can cause chronic conditions such as melanosis, hyperkeratosis, skin lesions, cancer, lung disease, and peripheral vascular disease ( 8 ). Cadmium (Cd), another heavy metal of concern, poses chronic and acute poisoning risks to workers exposed through ingestion and inhalation routes, leading to kidney and bone problems ( 9 ). Given the chronic and acute effects associated with heavy metals in soil, it is crucial to determine their concentration, which reflects their environmental input ( 10 ). Annually, a substantial number of heavy metals is generated and released into the environment from industrial factories, domestic waste, and chemical and agricultural sources ( 11 ). Landfill sites are of particular importance when it comes to heavy metal pollution ( 12 ). Landfilling has been favored over other methods due to its simplicity, cost-effectiveness, and relatively lower technological requirements. However, if landfill operations lack a leachate liner and an appropriate leachate collection system, they pose irreparable risks to soil and the underground water table (13). Waste leachate, a combination of organic materials, heavy metals, and other inorganic substances, is a threat to the environment and public health ( 14 ). Landfills receive a wide range of waste materials, including industrial, medical, electrical, plastic, glass, battery, paper, hazardous substances, and organic pollutants. Improper management of these wastes can lead to contamination of water, soil, and sediment, posing a threat to human health and that of other living organisms ( 15 ). Humans are commonly exposed to heavy metal hazards in surface soils through three primary routes: inhalation of suspended dust, ingestion, and dermal contact ( 16 ). Due to their long-lasting effects and inability to decompose, heavy metals accumulate in both the environment and humans ( 17 ). The lack of regulations, improper municipal solid waste management, and unplanned waste disposal can exacerbate some ecological and health issues ( 18 ). Population development in the Shiraz metropolis has raised municipal solid waste production, which has raised leachate levels in the city's landfill site. The major objective of this study was 1- To determine the concentration of heavy metals in the landfill soil of Shiraz City and its surrounding areas. 2- To analyze the physical and chemical properties of the soil at the landfill site and its surroundings in Shiraz City. 3- To assess the accumulation rate of heavy metals in the landfill soil and the surrounding soils of Shiraz city landfill using indicators such as ecological risk, health risk, pollution load index, and pollution index. 2. Materials and methods 2.1 Site description Shiraz is in the middle of the province of Fars, in the mountainous Zagros region, with a temperate climate. Situated at a height of 1500 meters above sea level. The location of the city is in latitude 29°33´ to 29°41´ and longitude 52°29´ to 52°36´. Shiraz, which has a population estimated at 1.5 million and a land area of 240 square kilometers, gets 337 mm of rainfall every year ( 19 ). The city's landfill is located on the Shiraz-Sarvestan axis in the Barm Shur-e neighborhood, 18 kilometers southeast of Shiraz. The entire area is 5000 hectares, with 40 hectares set aside for landfill, and is located at an altitude of around 1600 meters above sea level. Every day, 732.5 tons of materials entered Shiraz's waste landfill; 12.5 tons of those materials were separated and recycled, while the remaining 720 tons were buried there. The landfill site is located at 29°, 25° latitude and 52°, 42° longitude, and 1590 meters above sea level. locations used for sampling included: 1. Barm Shur-e Olya village 2. Leachate collection site 3. Active landfill site 4. Barm Shur-e Sofla village 5. Tayūn village 6. Healthcare waste landfill site 7. 1.5 kilometers from the landfill site 8. Future landfill site 9. Old landfill site 10. Recycling plant 11. Stone-cutting plant 12. Compost and vermicompost site. 2.2 Sample collection and analysis methods During the two seasons of winter (February 2022) and summer (July 2022) soil samples were collected at seven soil sampling stations at the landfill site in Shiraz City and five sampling stations in the residential area and surrounding the landfill from a depth of 0–20 cm (At each station, five soil subsamples were thoroughly combined to create only one composite sample) according to with ISO standard 10,381 (Fig. 1 )( 4 ). After drying in the open air in the room, To analyse every physical and chemical characteristic of the soil, the samples were passed through a 10 mesh (pore size 2 mm) sieve. To analyse heavy metals, the sieved samples underwent an additional sieving process with a 200 mesh (pore size 75µm) sieve. Subsequently, the samples were subjected to the Aqua Regia extraction method (a mixture of HCL and HNO 3 v/v 3:1) to extract heavy metals ( 20 ). The concentration of heavy metals was determined using a Varian 735 ICP-OES device. Soil pH was measured by mixing soil with deionized water (1:2 w/v) ( 21 ). A Metrohm 827 pH meter was used to measure the pH. Soil and deionized water were combined to determine the EC of the soil (1:5 w/v) ( 22 ). Using an EC meter model Cond 720, the EC measurement was performed. In order to assess the amount of organic matter in the soil, the furnace was used to burn soil samples for 4 hours at a temperature of 450 ◦C (loss on ignition) ( 23 ). The exchangeable cation substitution method was utilized to determine the soil's CEC using sodium acetate. Then, using a flame photometer to read the generated solution and compare it to the standard curve, the concentration of the solution sample was ascertained ( 24 ). To measure the temperature and moisture content, we three times vertically inserted the portable instrument (AMT-300, AMTAST, China) into the soil mass, down to a depth of 20 cm ( 25 ). 2.3 Pollution indicators 2.3.1 Pollution index (PI) This indicator determines the level of soil pollution ( 27 ). PI= \(\frac{{C}_{i}}{{c}_{ri}}\) where Ci is the concentration of HMs (mg/kg) and \({\text{c}}_{\text{r}\text{i} }\) is the background or geochemical background value of the HMs (mg/kg) element in the average Earth’s crust 2.3.2 Pollution Load Index (PLI) Tomlinson et al. (1980) introduced it. Utilizing the pollution load index, one can assess how much the environment has altered the concentration of heavy metals in soil. This index is calculated using the relationship below: ( 28 ). Table 1 showed Pollution indices and Pollution load indices classifications. 𝑃𝐿𝐼 = \(\sqrt[n]{PI1 \times PI2 \times PI3 \times \dots PIn}\) Table 1 Pollution indices and Pollution load indices classifications Classification PI contamination PLI level a. Pl < 1 Low 0–1 Low b. 1 ≤ PI < 3 Moderate 1–2 Moderate c. 3 ≤ PI 5 Extremely high 2.3.3 Ecological risk assessment Håkanson was its originator. \({E}_{r}^{i}\) is the ecological risk associated with each metal and ERI is the environmental ecological risk index ( 27 ). Tables 2 and 3 showed Ecological Risk Classification and Background values (Cri), Toxicity response factor (Tri), and world soil average in soil Table respectively. \({E}_{r}^{i}\) = 𝑇 𝑟𝑖 . 𝑃𝐼 𝑖 ( 2 ) ERI = \({\sum }_{i=1}^{n}{E}_{ri}\) Table 2 Ecological Risk Classification \({E}_{r}^{i}\) \({E}_{r}^{i}\) ERI ecological risk \({E}_{r}^{i}\) <40 Low ERI < 150 Low 40 \(\le {E}_{r}^{i}\) <80 Moderate 150 ≤ ERI < 300 Moderate 80 \(\le {E}_{r}^{i}\) <160 represents High 300 ≤ ERI < 600 High 160 \(\le {E}_{r}^{i}\) <320 High ERI ≥ 600 Extremely high \({E}_{r}^{i}\ge 320\) extremely strong Table 3 Background values (C ri ), Toxicity response factor (T ri ), and world soil average in soil Table Element (mg/kg) As Cd Cr Ni Cu Co Reference Cri 1.9 0.13 22 15 30 7 Turekian and Wedepohl(1961) 26 Tri 10 30 2 5 5 2 Håkanson (1980) 27 World soil average 6 0.35 70 50 30 8 Martin and Whitfield (1983) 29 2.3.4 Health risk assessment The US-EPA model states that exposure to heavy metals in soil is determined by chronic daily intake absorption (CDI) (mg kg − 1 day − 1 ) using equations 1–3 below: ( 30 , 31 , 32 ). ( 1 ) CDI Ingest = [(Ci × IngR × FC × EF × ED)/(BW× AT)] ( 2 ) CDI Inhale = [(Ci × InhR × EF × ED)/(PEF × BW× AT)] ( 3 ) CDI Dermal = [(Ci × SA × FC × AF × ABS × EF × ED)/(BW× AT)] CDI Total = CDI Ingest + CDI Inhale + CDI Dermal Where CDI (mg kg − 1 day − 1 ) is the Chronic daily intake via Ingestion (CDI Ingest ), Inhale (CDI Inhale ), Dermal contact (CDI Dermal ) and Ci is the concentration of heavy metal (mg/kg) IngR: ingestion rate, EF: exposure frequency, ED: exposure duration (year) BW: Body weight, AT is the time period over which the dose is averaged (day), FC: Conversion factor (unitless), InhRsoil is the inhalation rate (m 3 d − 1 ), PEF is the Particulate emission factor, AF: Adherence factor ABS: Applied dose absorbed across the skin (unitless)(Table 4 ). Table 4 Values of factors used in the risk assessment formulae. Factors (units) Value References Adult Children IngR (mg. day − 1 ) 100 200 33 EF (days. year − 1 ) 350 350 33 ED (year) 24 6 3 BW (kg) 56.8 15.9 33 AT ca (days) 70×365 70×365 33 AT nc (days) ED×365 ED×365 33 SA (cm 2 ) 1530 860 33 AF (mg. cm − 2 ) 0.49 0.65 33 InhR (m3.day) 20 7.65 33 FC (kg⋅mg − 1 ) 10 − 6 10 − 6 33 ABS 0.001 0.001 33 PEF (m 3 . kg) 1.36 × 10 9 1.36 × 10 9 33 USEPA 2002 USDOE 2011 Eziz (2018) (HQ) shows the Hazard Quotient of non-cancerous diseases for each heavy metal of the Hazard index according to the following equation: HQ = \(\frac{{CDI}_{total}}{RfD}\) where RfD represents the reference value (mg kg − 1 day − 1 ), according to the health risk assessment of the total heavy metals, then the non-carcinogenic cumulative Hazard index (HI) is calculated using the relationship below: HI = ΣHQ = HQ Ingest + HQ Inhale + HQ Dermal If HI 1, the possibility of non-cancerous disease effects with increasing HI value increase. The probability of developing any type of cancer during a lifetime due to exposure to carcinogenic risks is represented by Cancer risk (CR). For the studied metals, it is calculated according to the following equations, which is the sum of the cancer risk for all three pathways. CR = CDI × CSF TCR = ΣCR = CR Ingest + CR Inhale + CR Dermal where TCR for the total carcinogenic risk, and CR for the carcinogenic risk (unitless) and SF is the heavy metals' carcinogenic slope factor (mg kg − 1 d − 1 ). Table 5 shown reference dose (RfD) and slope factor (SF) of heavy metals for health risk assessment. If the total cancer risk is less than 1×10 − 6 (probability of one person in a million), it does not have significant effects on human health and this risk is negligible, while the total cancer risk is greater than 1×10 − 4 is unacceptable and dangerous for human health. The total cancer risk value between 1×10 − 4 and 1×10 − 6 indicates risk acceptable or tolerable. Table 5 Reference dose (RfD) and slope factor (SF) of heavy metals for health risk assessment. Element Oral RfD Dermal RfD RfD Inhalation Oral SF Dermal SF Inhalation SF Reference As 0.0003 0.000123 0. 3 1.5 3.66 15.1 34 Cd 0.001 0.00001 0.001 6.1 - 6.3 33 Ni 0.02 0.00540 0.0206 1.7 42.5 0.84 34 Cr 0.003 0.003 0.0000286 0.5 20 42 35 Cu 0.04 0.012 0.04 - - - 35, 33 2.4 Statistical analysis The statistical tests performed in this study include the Kolmogorov-Smirnov and Shapiro-Wilk test (p-value < 0.05) to assess the normality of the data, the non-parametric Mann-Whitney U test for non-normal data, independent t-test analysis for Comparison of heavy metals that are normal. Also, SPSS version 27 software was used to perform statistical tests. The Spearman correlation test was used to determine the correlation of the concentration of the measured elements; Finally, heavy metal concentration zoning was done using Arc-GIS version 10.8.2 software and the Inverse Distance Weighting (IDW) method. 3. Results and Discussion 3.1 Concentration and distribution of heavy metals in soil This study found that the average concentration of heavy metals in the landfill soil of Shiraz City and the nearby residential areas was Ni > Cr > Cu > Co > As > Cd (Fig S1 , S2). It shows that the patterns of heavy metal change in the two research areas are similar (Fig. 2 ). The share of these heavy metals in landfill soil was equal to 42.20%, 29.06%, 17.42%, 7.24%, 3.95%, and 0.13 for Ni, Cr, Cu, Co, As, and Cd metals, respectively; while in a similar study by Thongyuan et al. (2021) in Central, Thailand, the average concentration of heavy metals in the form of Al > Fe > Mg > Mn > Zn > Cu > bi > Cr > Pb > la > Ni > Co > Ga > Cd ( 36 ), and in a similar study by Adamcová et al. (2017) in the Czech Republic, the average concentration of heavy metals was as Fe > Mn > Cr > Ni > Co > Zn > Co > Pb > Cd > Hg ( 37 ). The soils of stone-cutting plant contained comparatively low amounts of metals, except for cadmium, copper, and cobalt. This was probably due to the area's low exposure to waste and little traffic. Furthermore, the soils in the waste separation plant region exhibited the highest concentration of heavy metals for all elements when compared to other areas. The higher concentration of heavy metals surrounding the recycling plant can be attributed to several factors, including improper handling of hazardous waste, illegal disposal of mixed trash, inadequate management practices, and the absence of leachate collection systems ( 38 ). In a study comparing two landfills, Closed and Active, Adelopo et al. concluded that the concentration of metals is higher in the Closed landfill ( 39 ). In our study, however, the daily soil coverage of the old and active landfill sites likely contributed to lower concentrations compared to the recycling plant. Among the different sites, the old landfill site exhibited the highest concentration of Ni metal, while the Active (current) landfill site showed the highest concentration of Co and As metals. The compost and vermicompost site had the highest concentration of Cd metal, and the site of Barm Shur-e Olya village had the highest concentration of Cu metal. Cadmium, a heavy metal, is commonly found in plastic waste, batteries, construction materials, and discarded tires that accumulate in landfills. Copper metal has applications as anti-erosion material in landfill sites and is found in electric parts, wires, and oils. Arsenic and its related compounds are found in pesticide, insecticide, and herbicide residues, as well as in lead, copper, and steel alloys manufactured for use in the electronics industry ( 40 ). Nickel is released into the environment by some human activities, such as burning fossil fuels, applying synthetic and biological fertilizers, extracting and smelting metal, disposing of garbage from homes, businesses, and cities, and using machine fuel ( 41 ). A comparison of elements concentration with the geochemical background concentration of heavy metals in the earth's crust and the world soil average standard shows that the average concentration of all elements, except for Cr, is higher than the average concentration of world soil and the average concentration of all metals is higher than the concentration of the geochemical background of heavy metals in the earth's crust. When comparing the average concentration of heavy metals in the adjacent residential areas to the municipal landfill in Shiraz, all the elements in the residential area have a lower concentration. Our results were consistent with those of studies conducted by Klinsawathom et al. in Thailand, Rinklebe et al. in Germany, and Karimian et al. in Iran. The soils surrounding the landfill were impacted, according to research, which is consistent with our results ( 37 , 42 , 43 ). In general, factors like rainfall, the amount of heavy metal deposition in the soil, the concentration of heavy metals in the leachate, and the length of time that heavy metals are absorbed determine how different the concentration of heavy metals is in landfill soil ( 44 ). The results of the Kolmogorov-Smirnov and Shapiro-Wilk tests show that the concentration of heavy metals, except for Cd, does not follow a normal distribution. (P-value < 0.05) (Fig S3). Non-parametric Mann-Whitney the U test was used to compare the concentrations of heavy metals in two seasons, with the exception of Cd. This test showed a statistically significant difference in the arsenic heavy metal between the two seasons (P-value = 009) (table S1 ). Independent t-test analysis was used to compare the Cd heavy metal, which is normal, in summer and winter (table S2). This test shows that there is no statistically significant difference in the amounts of Cd metal between summer and winter. (P-value < 0.05). 3.2 Determining the relationship between heavy metals and soil physical and chemical parameters High correlation coefficients (r) between different heavy metals can indicate that the metals were contaminated from the same source or that they went through similar chemical and physical processes. Statistically, if low (r ≤ 0.1), medium (0.1 < r ≤ 0.3), high (0.3 0.6) ( 45 ). The results showed that there is a very strong and significant positive relationship between heavy metals Cr-Ni (r = 0.86**p < 0.01), and Ni-Co (r = 0.766**p < 0.01). and between heavy metals Cr-Co (r = 0.561** p < 0.01), Cu-As (r = 0.475*p < 0.05), Co-As (r = 0.413*p < 0.05), had a strong and significant positive relationship. There was a strong and significant negative correlation between EC-Cr (r =-0.412* p < 0.05) and EC-pH (r =-0.519** p < 0.01) and no significant relationship was found with other metals. No significant relationship was found between heavy metals Cr, Ni, As and pH. Temperature has a strong and significant negative correlation with As (r =-0.481* p < 0.05), and pH (r =-0.582**p < 0.01). As-OC (r = 0.550*p < 0.01) has a strong and significant positive relationship, but with the temperature parameter (r =-0.694**p < 0.01) it has a very strong and significant, negative correlation. Cr-CEC (r = 0.721**p < 0.01), Ni-CEC (r = 0.683*p < 0.05), Co-CEC, (r = 0.707*p < 0.05) It has a very strong and significant positive relationship (Table 6 ). Table 6 The Spearman correlation analysis of metal concentration in the soil Variables Cr Cu Ni Co As Cd pH EC Temperature OC CEC Cr 1.0 Cu 0.121 1.0 Ni 0.860** 0.071 1.0 Co 0.561** 0.171 0.766** 1.0 As 0.297 0.475* 0.342 0.413* 1.0 Cd 0.046 0.339 -0.230 -0.395 -0.168 1.0 pH 0.342 -0.096 0.384 0.162 0.378 -0.152 1.0 EC -0.412* 0.190 -0.335 -0.148 -0.017 -0.047 -0.519** 1.0 Temperature -0.197 -0.216 -0.309 -0.076 -0.481* 0.163 -0.582** 0.061 1.0 OC 0.121 0.278 0.164 0.070 0.550** -0.246 0.306 -0.072 -0.694** 1.0 CEC 0.721** 0.159 0.683* 0.707* 0.049 -0.262 0.273 -0.322 0.175 -0.315 1.0 ** Correlation is significant at the 0.01 level (2-tailed). EC: electrical conductivity pH: power Hydrogen * Correlation is significant at the 0.05 level (2-tailed). CEC: Cation exchange capacity OC: organic carbon .Correlation is significant at the 0.05 level (p < 0.05) * There are different methods for interpolation in GIS. In this study, the IDW method was used. The result is shown in Fig. 3 for the landfill site and its surrounding residential areas. The interpolation results showed that station No.10 of the recycling plant site, as an anthropogenic source in the landfill site, has the most pollution. On the other hand, station No.8 of the future landfill site also shows low pollution and violet color due to the digging that took place in this station. Villages and residential areas (stations 5, 7, 11, 4, and 1) also showed a lower degree of pollution in the interpolation than the landfill site. 3.3 Physical and chemical characteristics of the soils Soil pH is one of the important factors that affect physical and chemical properties, biological pathways, and soil properties, as well as plant growth and biomass performance. Soil pH can control the dynamics bio, availability, and solubility of heavy metals. Also, soil pH affects the solubility of organic matter and the activity of soil microorganisms ( 46 ). The results of the measured pH in the soil showed that this characteristic has changed in the range of 7.29–8.21, its average is 7.8, and the soil of the region is alkaline. Meanwhile, the acidity of the leachate at the location of the leachate lagoon has been measured at 8.04 and the acidity of the leachate from the machinery entering the landfill has been measured at 3.35. The first sign of the methanogenic phase or mature leachate is a slightly high pH in the leachate analysis. According to Tchobanoglous et al. (1993), in new landfills, the pH is in the range of 4.5 to 7.5 and in the mature landfill, the pH is variable in the range of 6.6 to 7.5 ( 47 ). Zhou et al. stated that the results of pH ranged from 7.54 to 10.90 with an average of 8.59 ( 48 ). The high concentration of calcium in the analyzed samples confirms that the soil of the landfill site has carbonated compounds and causes the alkalinity of the soil created from them. EC values ranged from 242 to 5020 (µs/cm), and the highest EC value was found in the sampling station of Barm Shur-e Olya, with a value of 5020(µs/cm) in the summer season; when the EC of the soil reaches less than 200, it indicates a decrease in soil nutrients and as a result, a lack of nutrients for plant growth which causes a decrease in soil fertility. If the EC value reaches above 1600, it indicates high soil salinity ( 49 ). In Obiri-Nyarko et al., EC values were expressed in the range of 510–1454 (µs/cm) at the Kpone ( 17 ). Mirsal et al. concluded that the accumulation of heavy metals in plants occurs less in soil with lower EC ( 50 ). According to Rattan et al., one of the most important parameters in the soil nutrient cycle is soil organic carbon ( 51 ). Soil organic matter is one of the important factors in agriculture due to its effect on nutrient mineralization, soil microbial community structure, soil porosity, and water penetration, as well as water retention capacity, reduction of soil crust, and apparent density ( 52 , 53 ). OC values ranged from 0.24 to 2.58. Fig S4 and the average value was 1.09 and the highest OC value was found in the sampling station of the medical landfill in the winter season. Ideriah and (2001) Ibitoye mentioned that the increase of OM and OC in landfill soil is high due to high amounts of degradable waste materials ( 54 , 55 ). In the summer season, due to the stimulation of biological activity due to the increase in temperature, the CEC of the soil increases, and this increase in the cation exchange capacity can increase the precipitation and complexation of metals. Also, soil CEC plays a role in absorption and retention processes ( 56 , 57 ). CEC values ranged from 2.05 to 29.97 (meq/100g), and the average was 13.11(meq/100g), and the highest CEC value was found in the sampling station of the old landfill in the summer season (Fig. 4 ). In Fonge, B. A. et al., CEC values ranged from 9.61 to 16.20 in Cameroon ( 58 ). The average soil temperature during the two seasons was 27.5 ◦C; its highest value was 48 ◦C in the summer season, and its lowest value was 13 ◦C in the winter season. AMT-300 device qualitatively showed soil moisture as DRY in summer and Wet in winter. The results of the soil pollution index of the studied area show that the landfill site in Barm Shur-e Olya, Shiraz, has a low to very high degree of pollution. The findings indicated that the soils in the sampling station of the recycling plant show very high levels of pollution for all elements, and for copper metal in most of the stations, except for the station of the waste separation plant, the pollution index shows a low degree of pollution. The highest value of PI is related to As and Ni metal, and the lowest one is related to Cu metal (Table 7 ); among the reasons for these metals can be the leachate from waste and materials used in agriculture, which has a high concentration of heavy metals such as Cu, Cd, Ni, and Zn. Other uses of these metals can be mentioned as raw materials and products used in homes and fungicides, pesticides, as well as fertilizers and herbicides ( 58 ). In Mavakala et al., the results of the pollution index showed that the study site has low to very high pollution. For the elements of Co, Cu, Zn, Cd, Pb, Hg, and Cu, the value of the pollution index was greater than 1. The highest PI value was related to Zn metal, and the lowest value was related to Cr metal ( 16 ). In Hosseini Beinabaj et al., the value of the pollution index for all elements Pb, Cd, Mn, Ni, Cu, and Fe was less than 1, which shows a low-degree pollution index ( 45 ). Penetration of heavy metals in soil is expressed using the Pollution Load Index (PLI) parameter ( 59 ). The results of the pollution index of the sampling stations showed that the active landfill site, the old landfill site, and the sampling station of Tayūn Village had a high degree of pollution (2 < PLI < 3), and the rest of the stations had a medium degree of pollution. The reason for the low PLI in the medical landfill, despite the waste containing more metals, can be explained by the existence of a landfill based on the principles and compliance with scientific rules and the daily lime coating to reduce the spread of dust particles ( 38 ). In contrast, the site of the recycling plant shows a very high degree of pollution (PLI > 3). The reason for the high level of pollution in the recycling plant site can be attributed to the breakdown of various wastes in the landfill (waste separation plant) and heavy inputs of plastic, iron and glass ( 38 ). The average PLI in the analyzed soils is 2.58, which shows the high pollution of these soils. In a similar study by Sadeghi Poor Sheijany et al., the PLI for all stations had a pollution-low degree (PLI 1 for soil from the Ewhere landfill in Nigeria, which was consistent with the results of the present study at many stations ( 61 ). Table 7 The values of Pl and PLI for various soil sampling points Pl Sampling points Cr Cu Ni Co As Cd PLI Level 1 1.80 1.65 3.74 1.29 2.35 2.31 2.06 High level 2 2.03 0.67 4.4 1.65 2.40 1.74 1.85 Moderate 3 1.85 1.22 4.47 2.15 3.16 1.58 2.18 High level 4 2 0.72 4.27 1.5 2.22 1.89 1.83 Moderate 5 1.96 0.87 3.74 1.43 2.19 1.97 1.84 Moderate 6 2.23 0.62 4.87 1.5 2.08 1.85 1.84 Moderate 7 1.71 0.7 3.5 1.29 2.43 1.97 1.71 Moderate 8 1.91 0.62 4.3 1.65 1.98 1.77 1.52 Moderate 9 2.30 0.79 4.94 1.93 2.40 1.77 2.04 High level 10 11 5.29 22.8 8.08 22.82 6.35 10.76 Extremely high 11 1.37 0.77 2.6 1.43 1.69 1.97 1.53 Moderate 12 1.98 1.05 3.8 1.29 1.79 2.66 1.90 Moderate 3.4 Ecological Risks The results of the ecological risk index (E ri ) are shown in Table 8 . The assessment of the ecological risk of heavy metals in the area showed Cd and As have an important role in determining the ecological risk in the landfill site in Shiraz and the surrounding areas. The heavy metals As, Co, Cr, Cu, Ni, and Cr have low ecological risk potential (E ri < 40), while Cd has a medium ecological risk index (80 ≤ Eri < 40). The ERI index for residential areas and all other landfill investigation sites are in the low pollution class, except for the location of the recycling plant, which has extremely high pollution. These results are consistent with those of Sadeghi Poor Sheijany et al., who reported that the soil at the Saravan landfill site in Gilan, Iran, has an E ri of less than 40 for Pb, Zn, Cu, and Cr. The assessment of the ecological risk of metals in the area showed that As, Hg, and Cd were important metals in determining the ecological risk in the areas surrounding the Saravan landfill site. The average value of the ERI indicated a Moderate level of pollution ( 60 ). In Wang et al. (2020) study, the ERIs elements varied from 46.72 to 482.43. It was found that 42% of the landfill site and 58% of the landfill site had high risk and moderate risk, respectively. It was also shown that the enhanced environmental risk is due to a higher concentration of As and Hg elements ( 4 ). Table 8 The values of \({\varvec{E}}_{\varvec{r}}^{\varvec{i}}\) and ERI for various soil sampling points Sampling points As Cd Co Cr Cu Ni ERI Level 1 23.5 69.3 2.58 3.6 8.25 18.7 125.93 Low 2 24 52.2 3.3 4.06 3.35 22 108.91 Low 3 31.6 48 4.3 3.7 6.1 22.35 116.05 Low 4 22.1 56.7 3 4 3.6 21.35 110.85 Low 5 21.9 59.1 2.86 3.92 4.35 18.7 110.83 Low 6 20.8 5.55 3 4.46 3.1 24.35 61.26 Low 7 24.3 59.1 2.58 3.42 3.5 17.5 110.4 Low 8 19.8 53.1 3.3 5.88 3.1 21.5 106.68 Low 9 24 53.1 3.86 4.6 3.95 24.7 114.21 Low 10 228.2 190.5 16.16 22 26.45 114 597.31 Very high 11 16.9 59.1 2.86 2.74 3.85 13 98.45 Low 12 17.9 79.8 2.58 3.96 5.3 19 128.54 Low 3.5 Health Risks 3.5.1 Non-carcinogenic Risk The non-carcinogenic risk for adults and children in the study area is calculated using all three ways of ingestion, inhalation, and dermal contact in Tables S3, S4. Acceptable values were found for both HQ and HI (HQs < 1, HI) in residential areas and landfill sites. Therefore, there is no non-carcinogenic risk of the investigated metals for children and adults (Fig. 5). The non-carcinogenic risk assessment indicates that ingestion is the main source of exposure; for all metals in both age groups, the highest and lowest HQ values are HQ ingestion > HQ dermal > HQ inhalation. The total HI values for heavy metals in the soil samples of the study area were calculated as 0.3933 and 0.0854 for adults and children, respectively. These results indicate that children have a four times higher non-cancer risk than adults. This is because children are more likely to be exposed to heavy metals due to their physiological and behavioral characteristics, such as running, bouncing, playing in the soil, sucking on fingers, toys, and heavy breathing ( 62 ). 3.5.2 Carcinogenesis Risks In Tables S5 and S6, the daily exposure to the carcinogenic risk of heavy metals studied are shown; also, in Tables 9 and 10 , the risk of carcinogenicity of As, Cd, Cr, and Ni heavy metals through the three routes of ingestion, inhalation, and dermal contact for children and adults in landfill soil and surrounding residential areas is stated. Ni metal and the children age group showed the highest risk of carcinogenesis in the soil of the landfill site and its residential areas. For nickel metal, the value of risk carcinogenesis is 1.98×10 − 4 in landfill soil and 1.005×10 − 4 in residential areas, respectively, for children. , in the pathway of ingestion. The carcinogenic risk of heavy metals studied both in Shiraz landfill and its residential areas was as follows: Ni > Cr > As > Cd. The TCR values for heavy metals in landfill site soil were 2.57×10 − 4 for children and 1.60×10 − 4 for adults. which is more than 1×10 − 4 and is unacceptable and dangerous for human health. The TCR values of heavy metals in the soil surrounding the landfill and residential areas were 1.30×10 − 4 for children and 9.17×10 − 5 for adults. For children, this is higher than 1×10 − 4 , which is unsuitable for human health. It isn't safe. In contrast, the range of risks for adults is 1×10 − 6 to 1×10 − 4 , indicating an acceptable or tolerable risk. The elements under study in the landfill Shiraz do not present a non-carcinogenic risk, thus it is critical to concentrate on the long-term, chronic impacts of these metals and how they influence adults and children. Also, as the recycling plant workers come into direct touch with the heavy metal pollution there, particular consideration should be given to their well-being, including the creation of rest areas specifically designed for them. In the study by Karimian et al. (2021) in Tehran, Iran, the hazard index (HI) value was 6.5 times higher in children than in adults; nonetheless, this value was at a safe level for both landfill workers and residents of the target area (HI < 1), which was consistent with our results ( 38 ). Obiri-Nyarko et al. reported that for all routes, the ingestion route HI was 1.72, higher than the recommended threshold of 1. And the TCR is higher than the limit for both adults (8.54×10 − 4 ) and children (6.19×10 − 3 ). Also, the risk of cancer was higher in adults and children with arsenic than with lead ( 18 ). whereas, nickel in our study had the greatest impact on the risk of carcinogenesis in both the adult and child groups Table 9 The carcinogenic risk index of heavy metals in the area surrounding the Shiraz landfill CR ingest CR inhale CR dermal CR total Adults Children Adults Children Adults Children Adults Children As 3.57E-06 6.37E-06 5.28E-09 1.79E-09 6.51E-08 4.35E-08 3.64E-06 6.41E-06 Cd 9.21E-07 1.64E-06 1.44E-10 4,79E-11 - - 9.21E-07 1.64E-06 Cr 1.12E-05 2.005. E-05 1.38E-07 4.73E-08 3.36E-06 2.24E-06 1.46E-05 2.23E-05 Ni 5.25E-05 9.40E-05 3.82E-09 1.30E-09 2.01E-05 6.54E-06 7.26E-05 1.005E-04 Adults Children Total 9.17E-05 1.30 E-04 Table 10 The carcinogenic risk index of heavy metals in the soil from the Shiraz landfill CR ingest CR inhale CR dermal CR total Adults Children Adults Children Adults Children Adults Children As 8.61E-06 1.53E-05 1.27E-08 4.34E-09 1.57E-07 1.04E-07 8.77E-06 1.54E-05 Cd 1.12E-06 2.01E-06 1.71E-10 5.85E-11 - - 1.12E-06 2.01E-06 Cr 2.11E-05 3.78E-05 2.61E-07 8.90E-08 6.34E-06 4.22E-06 2.77E-05 4.21E-05 Ni 1.04E-04 1.85E-04 7.59E-09 2.58E-09 1.95E-05 1.30E-05 1.23E-04 1.98E-04 Adults Children Total 1.60E-04 2.57 E-04 El Fadili et al.'s study in Morocco (2022) reported that the hazard index (HI) levels for elements were higher than the safe threshold (HI > 1) for children. Likewise, the total carcinogenic risks of Pb and Cd for each group are less than the EPA threshold, indicating an acceptable level of carcinogenic risk. Many researchers have reported that arsenic is the main cause of both carcinogenic and non-carcinogenic concerns in their previous research, which is inconsistent with our findings. Most likely, the causes are the relatively high arsenic concentration in the soil and/or low Rfd. Exposure to high arsenic concentrations can have negative effects on human health, including cancers of the skin, lungs, prostate, bladder, liver, and other organs, as well as diseases of the skin, reproductive system, circulatory system, neurological system, and heart ( 17 ). The results of this study indicated that Ni was the main source of carcinogenic risks. Children who work near the residential areas of the Shiraz City landfill and the workers at the landfill site may have negative effects such as coughing, lung cancer, headaches, nausea, vomiting, stomach issues, visual, discomfort, pain, and dizziness ( 64 ). Consistent with our findings, other studies have reported that ingesting soil exposure individuals to carcinogenic and noncarcinogenic risks ( 17 , 38 , 60 , 65 ). In contrast to dermal contact, leading to allergic reactions and skin inflammation, ingesting metals damages the mucosal tissue of the gastrointestinal tract and can induce both acute and chronic liver disorders ( 65 ). 4. Conclusion This research aimed to assess the concentrations and risk assessments of heavy metals in the soil at different Shiraz landfill sites, together with the influence of these metals on the surrounding soils of the landfills. The results of the research showed that the average concentration of heavy metals in the landfill in Shiraz, Iran, and the surrounding areas was Ni > Cr > Cu > Co > As > Cd. The Recycling plant area's soil has the highest concentration of heavy metals of all elements compared to other areas. These metals' high concentration can be attributed to a variety of waste sectors at the waste separation plant site, such as organic materials, glass, batteries, paper, plastic, electronic trash, and industrial waste. According to the results of the pollution load index, there is a high level of pollution in the sample stations in the old landfill, the active landfill, and the village of Barm Shur-e Olya. There is also a very high level of pollution in the recycling plant sample station. In the surrounding residential areas of the landfill site, children who work and even other children are at risk of carcinogenesis, and the carcinogenic risk for adults is within the tolerable or acceptable range. However, the total carcinogenic risk (TCR) of heavy metals studied in the landfill soil for workers and children was more than 1×10 − 4 and unacceptable and harmful to human health. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments The authors would like to acknowledge the Department of Studies and Research, Shiraz Municipality for their support and contribution to this study. We also thank Shiraz Waste Management Organization and all of the honorable personnel who work in the Department of the Organization. Appendix A. Supplementary data Supplementary data to this article can be found online at Funding information This work was supported by Shiraz University of Medical Sciences Approval Number Ethics [IR.SUMS.SCHEANUT.REC.1401.012] Data availability: Data is provided within the manuscript or supplementary information files. Author Contribution All authors wrote the main manuscript text and reviewed the manuscript." References Yang Q, Li Z, Lu X, Duan Q, Huang L, Bi J. A review of soil heavy metal pollution from industrial and agricultural regions in China: Pollution and risk assessment. Science of the total environment. 2018;642:690-700. Thakare M, Sarma H, Datar S, Roy A, Pawar P, Gupta K, et al. Understanding the holistic approach to plant-microbe remediation technologies for removing heavy metals and radionuclides from soil. Current Research in Biotechnology. 2021;3:84-98. Rahman Z, Mohan A, Priya S. Electrokinetic remediation: An innovation for heavy metal contamination in the soil environment. 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Speciation, contamination, ecological and human health risks assessment of heavy metals in soils dumped with municipal solid wastes. Chemosphere. 2021;262:128013 Additional Declarations No competing interests reported. Supplementary Files suplimentdata15.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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4320875","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":301581835,"identity":"e75a596d-89d1-461d-9c47-2ac267bebb41","order_by":0,"name":"Ali Ghandeharizadeh","email":"","orcid":"","institution":"shiraz university of medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Ghandeharizadeh","suffix":""},{"id":301581836,"identity":"f7a25de5-5c29-4bd4-9593-69e3af03f4ee","order_by":1,"name":"mansooreh 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sciences","correspondingAuthor":false,"prefix":"","firstName":"Narges","middleName":"","lastName":"Shamsedini","suffix":""}],"badges":[],"createdAt":"2024-04-25 02:17:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4320875/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4320875/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56674481,"identity":"3c0e9b87-ca76-426e-9c35-324a84ad81ba","added_by":"auto","created_at":"2024-05-17 15:38:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":368845,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area showing sampling points\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/2f620607d04d3a3cddc376fe.jpg"},{"id":56673867,"identity":"150c3029-333d-4757-9a15-ff740b412568","added_by":"auto","created_at":"2024-05-17 15:30:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":94808,"visible":true,"origin":"","legend":"\u003cp\u003eConcentrations of HMs (mg/kg) in two seasons at different Sampling points\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/c16208146f2d147d0f45404a.jpg"},{"id":56673871,"identity":"021a0544-c6b2-409f-8228-21df22bfcc2e","added_by":"auto","created_at":"2024-05-17 15:30:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":890087,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution Cd, Ni, Co, Cr, As, and Cu (mg/kg) in soils in the study area\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/d3fbfd2a40621fc4f9a001ea.jpg"},{"id":56673868,"identity":"fc5e4124-2005-4321-b3d5-be15943096c1","added_by":"auto","created_at":"2024-05-17 15:30:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":136504,"visible":true,"origin":"","legend":"\u003cp\u003eThe value of CEC (meq/100g) and temperature (°C) in 12 sampling stations\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/c58fa52e237c35c75c9540f7.jpg"},{"id":56673870,"identity":"0ba72ead-3092-4941-b341-35b731d42ae9","added_by":"auto","created_at":"2024-05-17 15:30:22","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":66441,"visible":true,"origin":"","legend":"\u003cp\u003eThe non-carcinogenic risk index of heavy metals in the soil and surroundings of the Shiraz landfill\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/f99760687b08561df00c22f0.jpg"},{"id":76676690,"identity":"926ff185-1e53-46b6-ab03-29ab5f1c207a","added_by":"auto","created_at":"2025-02-19 14:27:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3063437,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/56b1834c-668b-46a3-a2a3-8e6e7d1f70c4.pdf"},{"id":56673872,"identity":"eac2e851-c26a-4328-a26a-87e2ba70db41","added_by":"auto","created_at":"2024-05-17 15:30:23","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":377503,"visible":true,"origin":"","legend":"","description":"","filename":"suplimentdata15.docx","url":"https://assets-eu.researchsquare.com/files/rs-4320875/v1/0e57e910a1da01dabd0b51c3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAccumulation, contamination, health and ecological risk assessment of heavy metals in landfill soil: Case study of Shiraz city in the Middle East\u003c/p\u003e","fulltext":[{"header":"Highlights ","content":"\u003cul\u003e\n \u003cli\u003eThere was an unacceptable health risk for workers at landfill.\u003c/li\u003e\n \u003cli\u003eFor landfill workers, there was a danger of cancer.\u003c/li\u003e\n \u003cli\u003echildren who work and even other children who\u0026nbsp;are near landfills are susceptible to cancer.\u003c/li\u003e\n \u003cli\u003eThe soil in the vicinity of the recycling plant has the highest concentration of heavy metals.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eHeavy metals are considered environmental pollutants, consisting of metals and metalloids with a density\u0026thinsp;\u0026gt;\u0026thinsp;5 g/cm\u003csup\u003e3\u003c/sup\u003e. When heavy metals seep into the soil, they pose a major threat to human health, other animals, and the biosphere. These heavy metals can enter the human body through a variety of pathways, including dermal contact, absorption, inhalation, soil ingestion, and consumption of contaminated food (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Soil, which is composed of minerals, water, and air, is vital to our environment. In the world of today, soil pollution has equaled the importance of pollution from the air and water (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). One of the chronic consequences of heavy metal toxicity in soil is its effects on the human nervous system (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Specific heavy metals have been associated with various health concerns. For instance, nickel (Ni) exposure can lead to lung and nasal cavity cancers, allergies, rhinitis, and sinusitis (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Chromium (Cr), another heavy metal, has been linked to kidney disorders, skin sensitivity, and lung cancer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Copper (Cu) toxicity, resulting from an elevated copper concentration in the body, can cause chronic copper poisoning, respiratory tract and throat irritation, vomiting, diarrhea, delayed fetal growth, and an increased risk of Alzheimer's disease (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Arsenic (As), a well-known heavy metal, can cause chronic conditions such as melanosis, hyperkeratosis, skin lesions, cancer, lung disease, and peripheral vascular disease (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Cadmium (Cd), another heavy metal of concern, poses chronic and acute poisoning risks to workers exposed through ingestion and inhalation routes, leading to kidney and bone problems (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Given the chronic and acute effects associated with heavy metals in soil, it is crucial to determine their concentration, which reflects their environmental input (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Annually, a substantial number of heavy metals is generated and released into the environment from industrial factories, domestic waste, and chemical and agricultural sources (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Landfill sites are of particular importance when it comes to heavy metal pollution (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Landfilling has been favored over other methods due to its simplicity, cost-effectiveness, and relatively lower technological requirements. However, if landfill operations lack a leachate liner and an appropriate leachate collection system, they pose irreparable risks to soil and the underground water table (13). Waste leachate, a combination of organic materials, heavy metals, and other inorganic substances, is a threat to the environment and public health (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Landfills receive a wide range of waste materials, including industrial, medical, electrical, plastic, glass, battery, paper, hazardous substances, and organic pollutants. Improper management of these wastes can lead to contamination of water, soil, and sediment, posing a threat to human health and that of other living organisms (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Humans are commonly exposed to heavy metal hazards in surface soils through three primary routes: inhalation of suspended dust, ingestion, and dermal contact (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Due to their long-lasting effects and inability to decompose, heavy metals accumulate in both the environment and humans (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The lack of regulations, improper municipal solid waste management, and unplanned waste disposal can exacerbate some ecological and health issues (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Population development in the Shiraz metropolis has raised municipal solid waste production, which has raised leachate levels in the city's landfill site. The major objective of this study was 1- To determine the concentration of heavy metals in the landfill soil of Shiraz City and its surrounding areas. 2- To analyze the physical and chemical properties of the soil at the landfill site and its surroundings in Shiraz City. 3- To assess the accumulation rate of heavy metals in the landfill soil and the surrounding soils of Shiraz city landfill using indicators such as ecological risk, health risk, pollution load index, and pollution index.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Site description\u003c/h2\u003e \u003cp\u003eShiraz is in the middle of the province of Fars, in the mountainous Zagros region, with a temperate climate. Situated at a height of 1500 meters above sea level. The location of the city is in latitude 29\u0026deg;33\u0026acute; to 29\u0026deg;41\u0026acute; and longitude 52\u0026deg;29\u0026acute; to 52\u0026deg;36\u0026acute;. Shiraz, which has a population estimated at 1.5\u0026nbsp;million and a land area of 240 square kilometers, gets 337 mm of rainfall every year (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe city's landfill is located on the Shiraz-Sarvestan axis in the Barm Shur-e neighborhood, 18 kilometers southeast of Shiraz. The entire area is 5000 hectares, with 40 hectares set aside for landfill, and is located at an altitude of around 1600 meters above sea level. Every day, 732.5 tons of materials entered Shiraz's waste landfill; 12.5 tons of those materials were separated and recycled, while the remaining 720 tons were buried there. The landfill site is located at 29\u0026deg;, 25\u0026deg; latitude and 52\u0026deg;, 42\u0026deg; longitude, and 1590 meters above sea level. locations used for sampling included: 1. Barm Shur-e Olya village 2. Leachate collection site 3. Active landfill site 4. Barm Shur-e Sofla village 5. Tayūn village 6. Healthcare waste landfill site 7. 1.5 kilometers from the landfill site 8. Future landfill site 9. Old landfill site 10. Recycling plant 11. Stone-cutting plant 12. Compost and vermicompost site.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample collection and analysis methods\u003c/h2\u003e \u003cp\u003eDuring the two seasons of winter (February 2022) and summer (July 2022) soil samples were collected at seven soil sampling stations at the landfill site in Shiraz City and five sampling stations in the residential area and surrounding the landfill from a depth of 0\u0026ndash;20 cm (At each station, five soil subsamples were thoroughly combined to create only one composite sample) according to with ISO standard 10,381 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). After drying in the open air in the room, To analyse every physical and chemical characteristic of the soil, the samples were passed through a 10 mesh (pore size 2 mm) sieve. To analyse heavy metals, the sieved samples underwent an additional sieving process with a 200 mesh (pore size 75\u0026micro;m) sieve. Subsequently, the samples were subjected to the Aqua Regia extraction method (a mixture of HCL and HNO\u003csub\u003e3\u003c/sub\u003e v/v 3:1) to extract heavy metals (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The concentration of heavy metals was determined using a Varian 735 ICP-OES device. Soil pH was measured by mixing soil with deionized water (1:2 w/v) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A Metrohm 827 pH meter was used to measure the pH. Soil and deionized water were combined to determine the EC of the soil (1:5 w/v) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Using an EC meter model Cond 720, the EC measurement was performed. In order to assess the amount of organic matter in the soil, the furnace was used to burn soil samples for 4 hours at a temperature of 450 ◦C (loss on ignition) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The exchangeable cation substitution method was utilized to determine the soil's CEC using sodium acetate. Then, using a flame photometer to read the generated solution and compare it to the standard curve, the concentration of the solution sample was ascertained (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). To measure the temperature and moisture content, we three times vertically inserted the portable instrument (AMT-300, AMTAST, China) into the soil mass, down to a depth of 20 cm (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Pollution indicators\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Pollution index (PI)\u003c/h2\u003e \u003cp\u003eThis indicator determines the level of soil pollution (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePI=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{C}_{i}}{{c}_{ri}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003ewhere Ci is the concentration of HMs (mg/kg) and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{c}}_{\\text{r}\\text{i} }\\)\u003c/span\u003e\u003c/span\u003eis the background or geochemical background value of the HMs (mg/kg) element in the average Earth\u0026rsquo;s crust\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Pollution Load Index (PLI)\u003c/h2\u003e \u003cp\u003eTomlinson et al. (1980) introduced it. Utilizing the pollution load index, one can assess how much the environment has altered the concentration of heavy metals in soil. This index is calculated using the relationship below: (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showed Pollution indices and Pollution load indices classifications.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u0026#119875;\u0026#119871;\u0026#119868; =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\sqrt[n]{PI1 \\times PI2 \\times PI3 \\times \\dots PIn}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/div\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\u003ePollution indices and Pollution load indices classifications\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\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003econtamination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePLI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003elevel\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ea.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePl\u0026thinsp;\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026thinsp;\u0026le;\u0026thinsp;PI\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ec.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026le;\u0026thinsp;PI\u0026thinsp;\u0026lt;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConsiderable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ed.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePI\u0026thinsp;\u0026ge;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExtremely high\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=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Ecological risk assessment\u003c/h2\u003e \u003cp\u003eH\u0026aring;kanson was its originator. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e is the ecological risk associated with each metal and ERI is the environmental ecological risk index (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e showed Ecological Risk Classification and Background values (Cri), Toxicity response factor (Tri), and world soil average in soil Table respectively.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({E}_{r}^{i}\\)\u003c/span\u003e \u003c/span\u003e = \u0026#119879;\u003csub\u003e\u0026#119903;\u0026#119894;\u003c/sub\u003e. \u0026#119875;\u0026#119868;\u003csub\u003e\u0026#119894;\u003c/sub\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) ERI = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\sum }_{i=1}^{n}{E}_{ri}\\)\u003c/span\u003e\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\u003eEcological Risk Classification\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eecological risk\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\\({E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERI\u0026thinsp;\u0026lt;\u0026thinsp;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le {E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150\u0026thinsp;\u0026le;\u0026thinsp;ERI\u0026thinsp;\u0026lt;\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le {E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt;160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erepresents High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u0026thinsp;\u0026le;\u0026thinsp;ERI\u0026thinsp;\u0026lt;\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e160\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le {E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt;320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERI\u0026thinsp;\u0026ge;\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExtremely high\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({E}_{r}^{i}\\ge 320\\)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBackground values (C\u003csub\u003eri\u003c/sub\u003e), Toxicity response factor (T\u003csub\u003eri\u003c/sub\u003e), and world soil average in soil Table\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"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 \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElement\u003csub\u003e(mg/kg)\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTurekian and Wedepohl(1961) 26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eH\u0026aring;kanson (1980) 27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorld soil average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMartin and Whitfield (1983) 29\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=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4 Health risk assessment\u003c/h2\u003e \u003cp\u003eThe US-EPA model states that exposure to heavy metals in soil is determined by chronic daily intake absorption (CDI) (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) using equations 1\u0026ndash;3 below: (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) CDI \u003csub\u003eIngest =\u003c/sub\u003e [(Ci \u0026times; IngR \u0026times; FC \u0026times; EF \u0026times; ED)/(BW\u0026times; AT)]\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) CDI \u003csub\u003eInhale\u003c/sub\u003e = [(Ci \u0026times; InhR \u0026times; EF \u0026times; ED)/(PEF \u0026times; BW\u0026times; AT)]\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) CDI \u003csub\u003eDermal\u003c/sub\u003e = [(Ci \u0026times; SA \u0026times; FC \u0026times; AF \u0026times; ABS \u0026times; EF \u0026times; ED)/(BW\u0026times; AT)]\u003c/p\u003e \u003cp\u003eCDI \u003csub\u003eTotal\u003c/sub\u003e = CDI \u003csub\u003eIngest\u003c/sub\u003e + CDI \u003csub\u003eInhale\u003c/sub\u003e + CDI \u003csub\u003eDermal\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eWhere CDI (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) is the Chronic daily intake via Ingestion (CDI \u003csub\u003eIngest\u003c/sub\u003e), Inhale (CDI \u003csub\u003eInhale\u003c/sub\u003e), Dermal contact (CDI \u003csub\u003eDermal\u003c/sub\u003e) and Ci is the concentration of heavy metal (mg/kg) IngR: ingestion rate, EF: exposure frequency, ED: exposure duration (year) BW: Body weight, AT is the time period over which the dose is averaged (day), FC: Conversion factor (unitless), InhRsoil is the inhalation rate (m\u003csup\u003e3\u003c/sup\u003ed\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), PEF is the Particulate emission factor, AF: Adherence factor ABS: Applied dose absorbed across the skin (unitless)(Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003eValues of factors used in the risk assessment formulae.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFactors (units)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIngR (mg. day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEF (days. year\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e350\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e350\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eED (year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBW (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e56.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAT\u003c/b\u003e\u003csub\u003e\u003cb\u003eca\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e70\u0026times;365\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e70\u0026times;365\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAT\u003c/b\u003e\u003csub\u003e\u003cb\u003enc\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eED\u0026times;365\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eED\u0026times;365\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSA (cm\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1530\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e860\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAF (mg. cm\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInhR (m3.day)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFC (kg\u0026sdot;mg\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;6\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;6\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePEF (m\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e.\u003cb\u003ekg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.36 \u0026times; 10\u003c/b\u003e\u003csup\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.36 \u0026times; 10\u003c/b\u003e\u003csup\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eUSEPA 2002 USDOE 2011 Eziz (2018)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e(HQ) shows the Hazard Quotient of non-cancerous diseases for each heavy metal of the Hazard index according to the following equation:\u003c/p\u003e \u003cp\u003eHQ = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{CDI}_{total}}{RfD}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003ewhere RfD represents the reference value (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), according to the health risk assessment of the total heavy metals, then the non-carcinogenic cumulative Hazard index (HI) is calculated using the relationship below:\u003c/p\u003e \u003cp\u003eHI\u0026thinsp;=\u0026thinsp;ΣHQ\u0026thinsp;=\u0026thinsp;HQ \u003csub\u003eIngest\u003c/sub\u003e + HQ \u003csub\u003eInhale\u003c/sub\u003e + HQ \u003csub\u003eDermal\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eIf HI\u0026thinsp;\u0026lt;\u0026thinsp;1 (safe level), the person is not exposed to the possibility of an adverse health effect, in other words, it indicates the safety of HI of heavy metals, in contrast to HI\u0026thinsp;\u0026gt;\u0026thinsp;1, the possibility of non-cancerous disease effects with increasing HI value increase.\u003c/p\u003e \u003cp\u003eThe probability of developing any type of cancer during a lifetime due to exposure to carcinogenic risks is represented by Cancer risk (CR). For the studied metals, it is calculated according to the following equations, which is the sum of the cancer risk for all three pathways.\u003c/p\u003e \u003cp\u003eCR\u0026thinsp;=\u0026thinsp;CDI \u0026times; CSF\u003c/p\u003e \u003cp\u003eTCR\u0026thinsp;=\u0026thinsp;ΣCR\u0026thinsp;=\u0026thinsp;CR \u003csub\u003eIngest\u003c/sub\u003e + CR \u003csub\u003eInhale\u003c/sub\u003e + CR \u003csub\u003eDermal\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ewhere TCR for the total carcinogenic risk, and CR for the carcinogenic risk (unitless) and SF is the heavy metals' carcinogenic slope factor (mg kg \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e d \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shown reference dose (RfD) and slope factor (SF) of heavy metals for health risk assessment.\u003c/p\u003e \u003cp\u003eIf the total cancer risk is less than 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e (probability of one person in a million), it does not have significant effects on human health and this risk is negligible, while the total cancer risk is greater than 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e is unacceptable and dangerous for human health. The total cancer risk value between 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e and 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e indicates risk acceptable or tolerable.\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\u003eReference dose (RfD) and slope factor (SF) of heavy metals for health risk assessment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOral RfD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDermal RfD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRfD Inhalation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOral SF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDermal SF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eInhalation SF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0. 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0000286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\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-\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\u003e35, 33\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 \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe statistical tests performed in this study include the Kolmogorov-Smirnov and Shapiro-Wilk test (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) to assess the normality of the data, the non-parametric Mann-Whitney U test for non-normal data, independent t-test analysis for Comparison of heavy metals that are normal. Also, SPSS version 27 software was used to perform statistical tests.\u003c/p\u003e \u003cp\u003eThe Spearman correlation test was used to determine the correlation of the concentration of the measured elements; Finally, heavy metal concentration zoning was done using Arc-GIS version 10.8.2 software and the Inverse Distance Weighting (IDW) method.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Concentration and distribution of heavy metals in soil\u003c/h2\u003e \u003cp\u003eThis study found that the average concentration of heavy metals in the landfill soil of Shiraz City and the nearby residential areas was Ni\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;As \u0026gt;\u0026thinsp;Cd (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, S2). It shows that the patterns of heavy metal change in the two research areas are similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The share of these heavy metals in landfill soil was equal to 42.20%, 29.06%, 17.42%, 7.24%, 3.95%, and 0.13 for Ni, Cr, Cu, Co, As, and Cd metals, respectively; while in a similar study by Thongyuan et al. (2021) in Central, Thailand, the average concentration of heavy metals in the form of Al\u0026thinsp;\u0026gt;\u0026thinsp;Fe\u0026thinsp;\u0026gt;\u0026thinsp;Mg\u0026thinsp;\u0026gt;\u0026thinsp;Mn\u0026thinsp;\u0026gt;\u0026thinsp;Zn\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;bi\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;la\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;Ga\u0026thinsp;\u0026gt;\u0026thinsp;Cd (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), and in a similar study by Adamcov\u0026aacute; et al. (2017) in the Czech Republic, the average concentration of heavy metals was as Fe\u0026thinsp;\u0026gt;\u0026thinsp;Mn\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;Zn\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Cd\u0026thinsp;\u0026gt;\u0026thinsp;Hg (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The soils of stone-cutting plant contained comparatively low amounts of metals, except for cadmium, copper, and cobalt. This was probably due to the area's low exposure to waste and little traffic. Furthermore, the soils in the waste separation plant region exhibited the highest concentration of heavy metals for all elements when compared to other areas. The higher concentration of heavy metals surrounding the recycling plant can be attributed to several factors, including improper handling of hazardous waste, illegal disposal of mixed trash, inadequate management practices, and the absence of leachate collection systems (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). In a study comparing two landfills, Closed and Active, Adelopo et al. concluded that the concentration of metals is higher in the Closed landfill (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). In our study, however, the daily soil coverage of the old and active landfill sites likely contributed to lower concentrations compared to the recycling plant. Among the different sites, the old landfill site exhibited the highest concentration of Ni metal, while the Active (current) landfill site showed the highest concentration of Co and As metals. The compost and vermicompost site had the highest concentration of Cd metal, and the site of Barm Shur-e Olya village had the highest concentration of Cu metal. Cadmium, a heavy metal, is commonly found in plastic waste, batteries, construction materials, and discarded tires that accumulate in landfills. Copper metal has applications as anti-erosion material in landfill sites and is found in electric parts, wires, and oils. Arsenic and its related compounds are found in pesticide, insecticide, and herbicide residues, as well as in lead, copper, and steel alloys manufactured for use in the electronics industry (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Nickel is released into the environment by some human activities, such as burning fossil fuels, applying synthetic and biological fertilizers, extracting and smelting metal, disposing of garbage from homes, businesses, and cities, and using machine fuel (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). A comparison of elements concentration with the geochemical background concentration of heavy metals in the earth's crust and the world soil average standard shows that the average concentration of all elements, except for Cr, is higher than the average concentration of world soil and the average concentration of all metals is higher than the concentration of the geochemical background of heavy metals in the earth's crust. When comparing the average concentration of heavy metals in the adjacent residential areas to the municipal landfill in Shiraz, all the elements in the residential area have a lower concentration. Our results were consistent with those of studies conducted by Klinsawathom et al. in Thailand, Rinklebe et al. in Germany, and Karimian et al. in Iran. The soils surrounding the landfill were impacted, according to research, which is consistent with our results (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). In general, factors like rainfall, the amount of heavy metal deposition in the soil, the concentration of heavy metals in the leachate, and the length of time that heavy metals are absorbed determine how different the concentration of heavy metals is in landfill soil (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). The results of the Kolmogorov-Smirnov and Shapiro-Wilk tests show that the concentration of heavy metals, except for Cd, does not follow a normal distribution. (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig S3). Non-parametric Mann-Whitney the U test was used to compare the concentrations of heavy metals in two seasons, with the exception of Cd. This test showed a statistically significant difference in the arsenic heavy metal between the two seasons (P-value\u0026thinsp;=\u0026thinsp;009) (table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Independent t-test analysis was used to compare the Cd heavy metal, which is normal, in summer and winter (table S2). This test shows that there is no statistically significant difference in the amounts of Cd metal between summer and winter. (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Determining the relationship between heavy metals and soil physical and chemical parameters\u003c/h2\u003e \u003cp\u003eHigh correlation coefficients (r) between different heavy metals can indicate that the metals were contaminated from the same source or that they went through similar chemical and physical processes. Statistically, if low (r\u0026thinsp;\u0026le;\u0026thinsp;0.1), medium (0.1\u0026thinsp;\u0026lt;\u0026thinsp;r\u0026thinsp;\u0026le;\u0026thinsp;0.3), high (0.3\u0026thinsp;\u0026lt;\u0026thinsp;r\u0026thinsp;\u0026le;\u0026thinsp;0.6), and very strong interrelationship (r\u0026thinsp;\u0026gt;\u0026thinsp;0.6) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). The results showed that there is a very strong and significant positive relationship between heavy metals Cr-Ni (r\u0026thinsp;=\u0026thinsp;0.86**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and Ni-Co (r\u0026thinsp;=\u0026thinsp;0.766**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). and between heavy metals Cr-Co (r\u0026thinsp;=\u0026thinsp;0.561** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Cu-As (r\u0026thinsp;=\u0026thinsp;0.475*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), Co-As (r\u0026thinsp;=\u0026thinsp;0.413*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), had a strong and significant positive relationship. There was a strong and significant negative correlation between EC-Cr (r =-0.412* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and EC-pH (r =-0.519** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and no significant relationship was found with other metals. No significant relationship was found between heavy metals Cr, Ni, As and pH. Temperature has a strong and significant negative correlation with As (r =-0.481* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and pH (r =-0.582**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). As-OC (r\u0026thinsp;=\u0026thinsp;0.550*p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) has a strong and significant positive relationship, but with the temperature parameter (r =-0.694**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) it has a very strong and significant, negative correlation. Cr-CEC (r\u0026thinsp;=\u0026thinsp;0.721**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Ni-CEC (r\u0026thinsp;=\u0026thinsp;0.683*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), Co-CEC, (r\u0026thinsp;=\u0026thinsp;0.707*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) It has a very strong and significant positive relationship (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\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\u003eThe Spearman correlation analysis of metal concentration in the soil\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eCEC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNi\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.860**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.561**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.766**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.475*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.413*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.412*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.519**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTemperature\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.481*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.582**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.550**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.694**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCEC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.721**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.683*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.707*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.0\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** Correlation is significant at the 0.01 level (2-tailed). EC: electrical conductivity pH: power Hydrogen\u003c/p\u003e \u003cp\u003e* Correlation is significant at the 0.05 level (2-tailed). CEC: Cation exchange capacity OC: organic carbon\u003c/p\u003e \u003cp\u003e.Correlation is significant at the 0.05 level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) *\u003c/p\u003e \u003cp\u003eThere are different methods for interpolation in GIS. In this study, the IDW method was used. The result is shown in Fig.\u0026nbsp;3 for the landfill site and its surrounding residential areas. The interpolation results showed that station No.10 of the recycling plant site, as an anthropogenic source in the landfill site, has the most pollution. On the other hand, station No.8 of the future landfill site also shows low pollution and violet color due to the digging that took place in this station. Villages and residential areas (stations 5, 7, 11, 4, and 1) also showed a lower degree of pollution in the interpolation than the landfill site.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Physical and chemical characteristics of the soils\u003c/h2\u003e \u003cp\u003eSoil pH is one of the important factors that affect physical and chemical properties, biological pathways, and soil properties, as well as plant growth and biomass performance. Soil pH can control the dynamics bio, availability, and solubility of heavy metals. Also, soil pH affects the solubility of organic matter and the activity of soil microorganisms (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). The results of the measured pH in the soil showed that this characteristic has changed in the range of 7.29\u0026ndash;8.21, its average is 7.8, and the soil of the region is alkaline. Meanwhile, the acidity of the leachate at the location of the leachate lagoon has been measured at 8.04 and the acidity of the leachate from the machinery entering the landfill has been measured at 3.35. The first sign of the methanogenic phase or mature leachate is a slightly high pH in the leachate analysis. According to Tchobanoglous et al. (1993), in new landfills, the pH is in the range of 4.5 to 7.5 and in the mature landfill, the pH is variable in the range of 6.6 to 7.5 (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Zhou et al. stated that the results of pH ranged from 7.54 to 10.90 with an average of 8.59 (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). The high concentration of calcium in the analyzed samples confirms that the soil of the landfill site has carbonated compounds and causes the alkalinity of the soil created from them.\u003c/p\u003e \u003cp\u003eEC values ranged from 242 to 5020 (\u0026micro;s/cm), and the highest EC value was found in the sampling station of Barm Shur-e Olya, with a value of 5020(\u0026micro;s/cm) in the summer season; when the EC of the soil reaches less than 200, it indicates a decrease in soil nutrients and as a result, a lack of nutrients for plant growth which causes a decrease in soil fertility. If the EC value reaches above 1600, it indicates high soil salinity (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). In Obiri-Nyarko et al., EC values were expressed in the range of 510\u0026ndash;1454 (\u0026micro;s/cm) at the Kpone (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Mirsal et al. concluded that the accumulation of heavy metals in plants occurs less in soil with lower EC (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). According to Rattan et al., one of the most important parameters in the soil nutrient cycle is soil organic carbon (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Soil organic matter is one of the important factors in agriculture due to its effect on nutrient mineralization, soil microbial community structure, soil porosity, and water penetration, as well as water retention capacity, reduction of soil crust, and apparent density (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). OC values ranged from 0.24 to 2.58. Fig S4 and the average value was 1.09 and the highest OC value was found in the sampling station of the medical landfill in the winter season. Ideriah and (2001) Ibitoye mentioned that the increase of OM and OC in landfill soil is high due to high amounts of degradable waste materials (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). In the summer season, due to the stimulation of biological activity due to the increase in temperature, the CEC of the soil increases, and this increase in the cation exchange capacity can increase the precipitation and complexation of metals. Also, soil CEC plays a role in absorption and retention processes (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). CEC values ranged from 2.05 to 29.97 (meq/100g), and the average was 13.11(meq/100g), and the highest CEC value was found in the sampling station of the old landfill in the summer season (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In Fonge, B. A. et al., CEC values ranged from 9.61 to 16.20 in Cameroon (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). The average soil temperature during the two seasons was 27.5 ◦C; its highest value was 48 ◦C in the summer season, and its lowest value was 13 ◦C in the winter season. AMT-300 device qualitatively showed soil moisture as DRY in summer and Wet in winter.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results of the soil pollution index of the studied area show that the landfill site in Barm Shur-e Olya, Shiraz, has a low to very high degree of pollution. The findings indicated that the soils in the sampling station of the recycling plant show very high levels of pollution for all elements, and for copper metal in most of the stations, except for the station of the waste separation plant, the pollution index shows a low degree of pollution. The highest value of PI is related to As and Ni metal, and the lowest one is related to Cu metal (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e); among the reasons for these metals can be the leachate from waste and materials used in agriculture, which has a high concentration of heavy metals such as Cu, Cd, Ni, and Zn. Other uses of these metals can be mentioned as raw materials and products used in homes and fungicides, pesticides, as well as fertilizers and herbicides (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). In Mavakala et al., the results of the pollution index showed that the study site has low to very high pollution. For the elements of Co, Cu, Zn, Cd, Pb, Hg, and Cu, the value of the pollution index was greater than 1. The highest PI value was related to Zn metal, and the lowest value was related to Cr metal (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In Hosseini Beinabaj et al., the value of the pollution index for all elements Pb, Cd, Mn, Ni, Cu, and Fe was less than 1, which shows a low-degree pollution index (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Penetration of heavy metals in soil is expressed using the Pollution Load Index (PLI) parameter (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). The results of the pollution index of the sampling stations showed that the active landfill site, the old landfill site, and the sampling station of Tayūn Village had a high degree of pollution (2\u0026thinsp;\u0026lt;\u0026thinsp;PLI\u0026thinsp;\u0026lt;\u0026thinsp;3), and the rest of the stations had a medium degree of pollution.\u003c/p\u003e \u003cp\u003eThe reason for the low PLI in the medical landfill, despite the waste containing more metals, can be explained by the existence of a landfill based on the principles and compliance with scientific rules and the daily lime coating to reduce the spread of dust particles (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). In contrast, the site of the recycling plant shows a very high degree of pollution (PLI\u0026thinsp;\u0026gt;\u0026thinsp;3). The reason for the high level of pollution in the recycling plant site can be attributed to the breakdown of various wastes in the landfill (waste separation plant) and heavy inputs of plastic, iron and glass (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The average PLI in the analyzed soils is 2.58, which shows the high pollution of these soils. In a similar study by Sadeghi Poor Sheijany et al., the PLI for all stations had a pollution-low degree (PLI\u0026thinsp;\u0026lt;\u0026thinsp;1) (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), which is not consistent with the results of the present study. Dirisu et al. (2019) reported PLI\u0026thinsp;\u0026gt;\u0026thinsp;1 for soil from the Ewhere landfill in Nigeria, which was consistent with the results of the present study at many stations (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe values of Pl and PLI for various soil sampling points\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003ePl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSampling points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLevel\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\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHigh level\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\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\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\u003e1.85\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\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHigh level\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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\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\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\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\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHigh level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExtremely high\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\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=\"Section2\"\u003e \u003ch2\u003e3.4 Ecological Risks\u003c/h2\u003e \u003cp\u003eThe results of the ecological risk index (E\u003csub\u003eri\u003c/sub\u003e) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The assessment of the ecological risk of heavy metals in the area showed Cd and As have an important role in determining the ecological risk in the landfill site in Shiraz and the surrounding areas. The heavy metals As, Co, Cr, Cu, Ni, and Cr have low ecological risk potential (E\u003csub\u003eri\u003c/sub\u003e \u0026lt; 40), while Cd has a medium ecological risk index (80\u0026thinsp;\u0026le;\u0026thinsp;Eri\u0026thinsp;\u0026lt;\u0026thinsp;40). The ERI index for residential areas and all other landfill investigation sites are in the low pollution class, except for the location of the recycling plant, which has extremely high pollution. These results are consistent with those of Sadeghi Poor Sheijany et al., who reported that the soil at the Saravan landfill site in Gilan, Iran, has an E\u003csub\u003eri\u003c/sub\u003e of less than 40 for Pb, Zn, Cu, and Cr. The assessment of the ecological risk of metals in the area showed that As, Hg, and Cd were important metals in determining the ecological risk in the areas surrounding the Saravan landfill site. The average value of the ERI indicated a Moderate level of pollution (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). In Wang et al. (2020) study, the ERIs elements varied from 46.72 to 482.43. It was found that 42% of the landfill site and 58% of the landfill site had high risk and moderate risk, respectively. It was also shown that the enhanced environmental risk is due to a higher concentration of As and Hg elements (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\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\u003eThe values of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{r}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e and ERI for various soil sampling points\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSampling points\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eERI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e125.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\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\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e108.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\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\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e116.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\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\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e110.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\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\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e110.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\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\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e61.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e110.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e106.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e114.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e228.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e597.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e98.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e128.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\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=\"Section2\"\u003e \u003ch2\u003e3.5 Health Risks\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1 Non-carcinogenic Risk\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe non-carcinogenic risk for adults and children in the study area is calculated using all three ways of ingestion, inhalation, and dermal contact in Tables S3, S4. Acceptable values were found for both HQ and HI (HQs\u0026thinsp;\u0026lt;\u0026thinsp;1, HI) in residential areas and landfill sites. Therefore, there is no non-carcinogenic risk of the investigated metals for children and adults (Fig.\u0026nbsp;5). The non-carcinogenic risk assessment indicates that ingestion is the main source of exposure; for all metals in both age groups, the highest and lowest HQ values are HQ ingestion\u0026thinsp;\u0026gt;\u0026thinsp;HQ dermal\u0026thinsp;\u0026gt;\u0026thinsp;HQ inhalation. The total HI values for heavy metals in the soil samples of the study area were calculated as 0.3933 and 0.0854 for adults and children, respectively.\u003c/p\u003e \u003cp\u003eThese results indicate that children have a four times higher non-cancer risk than adults. This is because children are more likely to be exposed to heavy metals due to their physiological and behavioral characteristics, such as running, bouncing, playing in the soil, sucking on fingers, toys, and heavy breathing (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2 Carcinogenesis Risks\u003c/h2\u003e \u003cp\u003eIn Tables S5 and S6, the daily exposure to the carcinogenic risk of heavy metals studied are shown; also, in Tables\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, the risk of carcinogenicity of As, Cd, Cr, and Ni heavy metals through the three routes of ingestion, inhalation, and dermal contact for children and adults in landfill soil and surrounding residential areas is stated. Ni metal and the children age group showed the highest risk of carcinogenesis in the soil of the landfill site and its residential areas. For nickel metal, the value of risk carcinogenesis is 1.98\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e in landfill soil and 1.005\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e in residential areas, respectively, for children.\u003c/p\u003e \u003cp\u003e, in the pathway of ingestion. The carcinogenic risk of heavy metals studied both in Shiraz landfill and its residential areas was as follows: Ni\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;As \u0026gt;\u0026thinsp;Cd. The TCR values for heavy metals in landfill site soil were 2.57\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e for children and 1.60\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e for adults. which is more than 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e and is unacceptable and dangerous for human health. The TCR values of heavy metals in the soil surrounding the landfill and residential areas were 1.30\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e for children and 9.17\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e for adults. For children, this is higher than 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e, which is unsuitable for human health. It isn't safe.\u003c/p\u003e \u003cp\u003eIn contrast, the range of risks for adults is 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e to 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e, indicating an acceptable or tolerable risk. The elements under study in the landfill Shiraz do not present a non-carcinogenic risk, thus it is critical to concentrate on the long-term, chronic impacts of these metals and how they influence adults and children. Also, as the recycling plant workers come into direct touch with the heavy metal pollution there, particular consideration should be given to their well-being, including the creation of rest areas specifically designed for them. In the study by Karimian et al. (2021) in Tehran, Iran, the hazard index (HI) value was 6.5 times higher in children than in adults; nonetheless, this value was at a safe level for both landfill workers and residents of the target area (HI\u0026thinsp;\u0026lt;\u0026thinsp;1), which was consistent with our results (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Obiri-Nyarko et al. reported that for all routes, the ingestion route HI was 1.72, higher than the recommended threshold of 1. And the TCR is higher than the limit for both adults (8.54\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e) and children (6.19\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e). Also, the risk of cancer was higher in adults and children with arsenic than with lead (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). whereas, nickel in our study had the greatest impact on the risk of carcinogenesis in both the adult and child groups\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\u003eThe carcinogenic risk index of heavy metals in the area surrounding the Shiraz landfill\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCR \u003csub\u003eingest\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCR \u003csub\u003einhale\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eCR \u003csub\u003edermal\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eCR \u003csub\u003etotal\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.57E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.37E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.28E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.79E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.51E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.35E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.64E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.41E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.21E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.44E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,79E-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\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\u003e9.21E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.64E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.005. E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.73E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.36E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.24E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.46E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.23E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.25E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.40E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.82E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.01E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.54E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.26E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.005E-04\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\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.17E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30 E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\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=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe carcinogenic risk index of heavy metals in the soil from the Shiraz landfill\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCR \u003csub\u003eingest\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCR \u003csub\u003einhale\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eCR \u003csub\u003edermal\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eCR \u003csub\u003etotal\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.61E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.34E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.57E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.77E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.54E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.01E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.71E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.85E-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\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\u003e1.12E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.01E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.11E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.78E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.61E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.90E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.34E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.22E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.77E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.21E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.85E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.59E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.58E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.95E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.30E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.23E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.98E-04\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\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.60E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.57 E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEl Fadili et al.'s study in Morocco (2022) reported that the hazard index (HI) levels for elements were higher than the safe threshold (HI\u0026thinsp;\u0026gt;\u0026thinsp;1) for children. Likewise, the total carcinogenic risks of Pb and Cd for each group are less than the EPA threshold, indicating an acceptable level of carcinogenic risk. Many researchers have reported that arsenic is the main cause of both carcinogenic and non-carcinogenic concerns in their previous research, which is inconsistent with our findings. Most likely, the causes are the relatively high arsenic concentration in the soil and/or low Rfd. Exposure to high arsenic concentrations can have negative effects on human health, including cancers of the skin, lungs, prostate, bladder, liver, and other organs, as well as diseases of the skin, reproductive system, circulatory system, neurological system, and heart (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The results of this study indicated that Ni was the main source of carcinogenic risks. Children who work near the residential areas of the Shiraz City landfill and the workers at the landfill site may have negative effects such as coughing, lung cancer, headaches, nausea, vomiting, stomach issues, visual, discomfort, pain, and dizziness (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Consistent with our findings, other studies have reported that ingesting soil exposure individuals to carcinogenic and noncarcinogenic risks (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). In contrast to dermal contact, leading to allergic reactions and skin inflammation, ingesting metals damages the mucosal tissue of the gastrointestinal tract and can induce both acute and chronic liver disorders (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis research aimed to assess the concentrations and risk assessments of heavy metals in the soil at different Shiraz landfill sites, together with the influence of these metals on the surrounding soils of the landfills. The results of the research showed that the average concentration of heavy metals in the landfill in Shiraz, Iran, and the surrounding areas was Ni\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;As \u0026gt;\u0026thinsp;Cd.\u003c/p\u003e \u003cp\u003eThe Recycling plant area's soil has the highest concentration of heavy metals of all elements compared to other areas. These metals' high concentration can be attributed to a variety of waste sectors at the waste separation plant site, such as organic materials, glass, batteries, paper, plastic, electronic trash, and industrial waste. According to the results of the pollution load index, there is a high level of pollution in the sample stations in the old landfill, the active landfill, and the village of Barm Shur-e Olya. There is also a very high level of pollution in the recycling plant sample station. In the surrounding residential areas of the landfill site, children who work and even other children are at risk of carcinogenesis, and the carcinogenic risk for adults is within the tolerable or acceptable range. However, the total carcinogenic risk (TCR) of heavy metals studied in the landfill soil for workers and children was more than 1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e and unacceptable and harmful to human health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the Department of Studies and Research, Shiraz Municipality for their support and contribution to this study. We also thank Shiraz Waste Management Organization and all of the honorable personnel who work in the Department of the Organization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAppendix A. Supplementary data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary data to this article can be found online at\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Shiraz University of Medical Sciences Approval Number Ethics [IR.SUMS.SCHEANUT.REC.1401.012]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors wrote the main manuscript text and reviewed the manuscript.\"\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYang Q, Li Z, Lu X, Duan Q, Huang L, Bi J. A review of soil heavy metal pollution from industrial and agricultural regions in China: Pollution and risk assessment. 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Chemosphere. 2021;262:128013\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":"Ecological and health risk assessment, soil, landfill, Shiraz, Solid waste","lastPublishedDoi":"10.21203/rs.3.rs-4320875/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4320875/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePopulation concentration in metropolitan areas generates and disposes of substantial quantities of waste with varying compositions. Transporting this waste to landfills produces leachate, which causes harmful heavy metal pollution. In this study, seven soil sampling stations were established at Shiraz Engineering Landfill, with five additional stations near residential areas. Sampling occurred during low and high rainfall seasons. The Aqua Regia method determined heavy metal concentrations. The share of these heavy metals in landfill soil was as follows: 42.20% for Ni, 29.06% for Cr, 17.42% for Cu, 7.24% for Co, 3.95% for As, and only 0.13% for Cd metal. The average pollution load index in the analyzed soils was 2.58 and it showed the High level of pollution of these soils. The ecological risk index for residential areas and most landfill locations (excluding the recycling plant) fell within the low pollution category. The results of the non-carcinogenic risk assessment indicated that the hazard index (HI) for all heavy metals in the soil samples of the study area was 0.3933 for children and 0.0854 for adults. These values suggest that workers at the landfill site and children and adults residing near the site are not exposed to short-term risks associated with heavy metals. The chronic and long-term carcinogenic risk (TCR) for the studied heavy metals in the landfill soil exceeded the threshold of 1×10\u003csup\u003e-4\u003c/sup\u003e for both adults and children, indicating an unacceptable and dangerous risk to human health. For soil samples from residential areas, the TCR value for children was 1.30×10\u003csup\u003e-4\u003c/sup\u003e, indicating the risk of carcinogenesis specifically for children.\u003c/p\u003e","manuscriptTitle":"Accumulation, contamination, health and ecological risk assessment of heavy metals in landfill soil: Case study of Shiraz city in the Middle East","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-17 15:30:17","doi":"10.21203/rs.3.rs-4320875/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":"e40a7540-7a05-42c7-aba5-dc4fc48f1796","owner":[],"postedDate":"May 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":31864161,"name":"Earth and environmental sciences/Environmental sciences"},{"id":31864162,"name":"Earth and environmental sciences/Solid earth sciences"},{"id":31864163,"name":"Health sciences/Health occupations"}],"tags":[],"updatedAt":"2025-02-19T14:27:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-17 15:30:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4320875","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4320875","identity":"rs-4320875","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}