Modeling and identification of affective parameters on cadmium’s durability and evaluating cadmium pollution indicators caused by using chemical fertilizers in long term

Soil contamination by anthropogenic heavy metals has become a global issue. This study aimed to investigate cadmium (Cd) concentration, mobility, and contamination indices of Cd in soils in the Hamadan province, west of Iran. To investigate the concentration of Cd in soil, one hundred soil samples from wheat farms and five samples from control lands were collected. Pollution indexes, including Cd mobility, enrichment factor, geoaccumulation index, contamination index, and availability ratio, were investigated. The structural equation model was also used to evaluate effective parameters on cadmium durability in soil. Results showed that mean values of available phosphorus (P) were 83.65, 129, and 65 (mg kg−1) in three land-use types rainfed, irrigated, and controlled, respectively. The mean values of Cd in different land-use types of rainfed, irrigated, and controlled were 0.15, 0.18, and 0.08 (mg kg−1), respectively. The results indicated that the amount of Cd in both forms (available and total) in ones that received fertilizer, especially P fertilizers, was higher than in the controlled one. Other pollution indexes revealed that the study area had been slightly contaminated due to anthropogenic activities. Lime, clay, lead, and OM were identified as affective parameters on cadmium durability. Finally, the results demonstrated that the mobility rate was high. Cd had a higher potential mobility in soil samples in the rain-fed and irrigated land than in the controlled land, and Cd had a low retention time.


Introduction
Environmental contamination by heavy metals has been a growing concern over the last few decades in developing and developed countries (Zhang, 2009;Dodangeh et al., 2018;Briffa et al., 2020;Silva et al., 2021).Soil, water, and air significantly affect human health (Steffan et al., 2018;Zakaria et al., 2021).Soil is known as one of the essential natural resources for the human food supply.Natural sources and anthropogenic activities are releasing heavy metals into the soil environment.Soil contamination by anthropogenic heavy metals has been a major environmental problem.Anthropogenic activities can increase levels of heavy metals in agricultural soils, which can quickly transfer from soil to groundwater or crops, affecting plants, animals, and human health (Bolan et al., 2003;Yari et al., 2017).Solid waste disposal, sludge applications, vehicular exhaust, wastewater irrigation, industrial activities, and metal mining are the major sources of soil contamination by heavy metals (Khan et al., 2008;Lei et al., 2010;Singh et al., 2005).Also, regular agricultural practices generally cause the enrichment of heavy metals in soil (Rodriguez Martin et al., 2006).Chemical fertilizers, especially phosphate fertilizers, are one of the most important anthropogenic sources of soil contamination,.Different heavy metals in phosphate fertilizers are often due to the impurity in phosphate rocks.Fertilizer-induced pollutions of soils depend on the consumption rate, type of fertilizer, and farming history (Dharma-Wardana, 2018;Mahmud et al., 2021;Rapheal et al., 2007).
In recent years, concern regarding Cadmium (Cd) as a highly toxic heavy metal has been increasing (Jami Al-Ahmadi et al., 2018;Payandeh et al., 2018;Zhang et al., 2021).Cadmium enters the human body mainly via water, food, and respiration.Wheat is one of the most important crops grown for human consumption worldwide.For various reasons, Cd content in wheat grains has increased to 0.4 (mg kg −1 ) based on dry weight (more than four times the allowable limit) (Deng et al., 2020).The permissible concentration of Cd in wheat is 0.1 to 0.12 (mg kg −1 ) (Savaghebi et al., 2002), and the uptake of Cd by plants and ingestion by humans depends on the bioavailability of Cd in the soil (Rahimi et al., 2021;Yong, 2001).Heavy metals exist in soils in various forms with different bioavailability.
Investigating heavy metals in various fractions has become increasingly important in environmental studies while providing valuable information for metal remediation, mobility, and risk assessment.The mobility and bioavailability of heavy metals in soil are determined by their chemical forms (Jaradat et al., 2006;Pikuła & Stepien, 2021).The sequential extraction of soil Cd can be used to evaluate Cd behavior in soil and its availability in plants.Through the development of ecological environmental studies, significant amount of information related to heavy metal concentration in soils has been measured that can be applied to assess the quality of the ecological environment (Rahimi et al., 2021).Many methods have been presented to assess the environmental quality, such as contamination index, gray correlation, principal component analysis (Cheng et al., 2007), and fuzzy decision.So it is crucial to select an appropriate method to evaluate soil quality for decision-making and spatial planning.Determining the contamination indices of heavy metals is an important aspect that indicates the degree of risk of heavy metals to the environment concerning its retention time (Nemati et al., 2009).The contamination index is a powerful tool for processing and analyzing environmental information for decision-makers, managers, technicians, and the public (Caeiro et al., 2005;Nazarpour et al., 2019).The commonly used heavy metals contamination indices in soils were classified into single and integrated indices.The single indices contain tools that can be used only to assess soil pollution with particular heavy metals.Assessing the health risk of soil is a beneficial method of identifying contaminants and their exposure states.Regional studies can provide helpful information about heavy metal distributions originating from natural and anthropogenic resources (Gao et al., 2021;Pils et al., 2004;Xu et al., 2021).Although previous studies have been carried out to assess Cd's status and its chemical fractionation in soils, little research has been done on the Cd contamination index and its health risk potential to agricultural soils in Iran (Faraji et al., 2022;Jahandari, 2020;Keshavarzi et al., 2015;Mohseni-Bandpei et al., 2017).
The structural equation model is a very general and powerful multivariate analysis technique that belongs to the multivariate regression family.This model is an extension of the general linear model that allows the researcher to simultaneously test a set of regression Vol.: (0123456789) equations (Harkins et al., 1980).Therefore, it provides a flexible framework for testing a wide range of possible relationships between variables in the model, including mediating effects and confounding hidden variables.Moreover, at a more general level, this model's parameters can measure the contribution of each of the predictors in the covariance structure (Kupek, 2006).The structural equation model is based on the hypothesis that the measured variables produce a specific covariance structure with a continuous multivariate normal distribution.This method provides a comprehensive and flexible approach for research design, data analysis, simultaneous evaluation of measurement structures, and the structure of paths between these structures.In fact, this method provides enough flexibility to work simultaneously with multiple related equations and an accurate picture of causal relationships between key structures (Zhu et al., 2006).Structural equation modeling is a comprehensive statistical approach for testing hypotheses about the relationships between observed and latent variables, which sometimes is called structural analysis of covariance, causal modeling, and linear structural relations (Kline & Santor, 1999).Considering direct and indirect effects, in addition to the latent variable role in the structural equation model, this method provides a better understanding of the investigation process (Kline & Santor., 1999).
Hence, during a study in the Hamadan province, Rahimi et al. (2021) investigated the rate of Cd uptake in different sexes and ages, as well as the distribution of Cd.In this study, it was shown that Cd absorption is higher in women than men; with increasing age, Cd absorption has increased.Above all, due to the vital role of the bread in providing food to society, the amount of Cd entering the food basket of the households through wheat is of vital importance worldwide, especially in Iran.Therefore, it is necessary to use a set of different quantitative and qualitative methods of soil pollution assessment along with zoning procedures simultaneously to understand the extent of soil pollution.This paper studied the environmental and ecological pollution of Cd to human health in wheat farms in the Hamadan province.
Also, in the structural equation modeling field, no study has been done yet on the persistence of cadmium and other heavy and toxic metals in soil.
For this purpose, the pollution indices, including availability ratio, geoaccumulation index, enrichment factor, and contamination index, were investigated.Also, the structural equation model assessed how soil's parameters affect the cadmium's durability.

Study area
The study area, known as the Hamadan province, is located in the west of Iran, between longitudes 47°34' and 49°36' E and latitudes 33°59' and 35°48' N, and is about 19,548 km 2 (Fig. 1).

Sampling
Samples were from wheat farms affected by the frequent use of chemical fertilizers during the past decades.A completely randomized design was performed with four replicates.A hundred soil samples from wheat farms (84 soil samples from rainfed and 16 from irrigated fields) were collected and placed into labeled polyethylene bags.Also, five soil samples were collected from the uncultivated lands far from wheat (Triticum aestivum L.) farms as control samples.About 4.0 kg of soil samples were collected from each sampling site's topsoil (0-30 cm) using a stainless steel sampling tool and were transferred to the laboratory.First, the samples were air-dried, then disaggregated in a porcelain mortar and sieved (2 mm).
Soil pH was measured in a 1:5 soil-to-water ratio suspension by ohmmeter 744 pH meter (Thomas, 1996).The electrical conductivity (EC) of the soil samples was measured by the Roades (1996) method.Organic matter (OM) was determined by wet oxidation (Walkley & Black, 1934), and cation exchangeable capacity (CEC) was determined by the Bower procedure (Rowell, 1994).Particle size distribution (PSD) was obtained with the hydrometer method (Bauycos, 1962).Equivalent CaCO 3 was measured by the titration method (Sims, 1996), and calcium was measured by compelxometry method.

Experiments
Total P was determined by four normal nitric acid (HNO 3 , Merck, Germany) digestion methods (Sposito et al., 1982), and available P was measured by Vol.: (0123456789) the sodium bicarbonate (NaHCO, Merck, Germany) method (Olsen & Sommers, 1990).Soil available Cd and Pb concentrations were measured through the DTPA (diethylene triamine pentaacetic acid, Sigma-Aldrich, USA) extraction method (Lindsay & Norvell, 1979), and to determine total Cd content, soil samples were digested in 4 normal nitric acid 2 s (Sposito et al., 1982).The soil samples were extracted using the Sposito Sequential Extraction Method, as represented in Table 1.According to this procedure, four fractions, including soluble and exchangeable, organic, carbonate, and residual, were separated.The Cd concentration in the extracts was determined by the appropriate atomic absorption spectrometry (AAS) technique (Varian 220).Three different extraction conditions were used for each soil sample to determine the total and available concentrations.

Equipment
Atomic absorption spectrometer (AAS), Varian 220 model made in Australia, has a spectroscopic method to measure the amount of chemical elements, resulting from light absorption of atoms in gaseous phase.The basis of this method is the absorption of electromagnetic radiation of the atoms in an element.This method identifies more than 70 elements, having different accuracy in different elements.In this study, a Metrohm pH-meter made in Switzerland with measuring range of 1 to 14 and accuracy ±0.003/ ±0.2% mV/± 0.2 °C was used.EC meter used in this research was CON500 model made in Taiwan with 0.000 uS/cm−400 mS/cm measuring range, 0.001-0.1 resolution, and ±0.05% accuracy.Atomic absorption spectrometer (AAS) Varian 220 model, made in Australia, has a spectroscopic method to measure the amount of chemical elements resulting from light absorption of atoms in the gaseous phase.The basis of this method is the absorption of electromagnetic radiation of the atoms of an element.This method identifies more than 70 elements, having different accuracy in different elements.In this study, a Metrohm pH-meter made in Switzerland with a measuring range of 1 to 14 and an accuracy ± 0.003/ ± 0.2% mV / ± 0.2 °C was used.EC meter utilized in this research was a CON500 model made in Taiwan with 0.000 uS/cm-400 mS/cm measuring range, 0.001-0.1 resolution, and ± 0.05% accuracy..The film photometer was the Jenway PFP7 model, made in England with five filters for analysis of Na, K, Ba, Li, and Ca elements.Moreover, UV/Vis spectrophotometer, model 6850, made in England, with a wavelength resolution of 0.1 nm and a wavelength range of 1100-190 nm, was used.Hydrometer ASTM 152H-62, with a length of 280 mm and a concentration range of −5 to + 60, was also used to determine the soil texture.

Structural equation model (SEM)
Generally, analysis with the SmartPLS (partial least square) method consists of three parts of the measurement model, SEM, and general model.Variables of this method are in two different kinds obvious and hidden; Hidden variables are used in different stages.The measurement model includes the different dimensions and the parameters of each dimension.Analysis of the existing relation between parameters and dimensions is studied in this model.The SEM includes all the existing designs of the main model, and the correlation between different structures and the existing relations between them are studied in this part.The general model includes the measurement and SEM and evaluates their fitness.The evaluation of the model's fitness will be completed in the general model (Kline, 2015).

Cronbach's alpha and composite reliability
Table 2 shows Cronbach's alpha and composite reliability parameters.Composite reliability is introduced as a better method than the traditional method for reliability measurements by calculating Cronbach's alpha.Result shows that the composite reliability equal or greater than 0.7 is suitable.(Nunnally, 1978).This parameter is shown in the following table.Table 2 demonstrates that all the Cronbach's alphas and the composite reliability parameters are above 0.6 and 0.7, respectively, which means they are in a suitable reliability range.

The Sobel test
The Sobel test is also called multiplication of coefficient approach, delta method, or normal theory approach.This test is based on inference theory of direct effect to calculate the inference of indirect effect coefficient of "a × b".Normal assumption is used in the Sobel test to evaluate the related equation.The null hypothesis and the opposite hypothesis in this method are evaluated by having a standard error of indirect effect.The Z-value is calculated by Eq. ( 1) in which:a: path coefficient between the independent variable and the mediator variableb: path coefficient between the mediator variable and the dependent variable S a : standard error between the independent variable and the mediator variable.
S b : standard error between the mediator variable and the dependent variable. (1) The VAF index The whole or partial effect of the independent variable on the dependent variable is related to the mediator variable (Baron & David, 1986).VAF (variance accounted for) shows the portion of indirect effect on the total effect.c: direct path or direct effecta × b: indirect path or indirect effecta × b + c: total path or total effect.
When the indirect path is meaningful (a, b, and their multiplication is meaningful), the VAF can be evaluated.If the VAF is less than 0.2, it does not have the mediator effect, if it is between 0.2 and 0.8, the mediator effect is negligible, and if this value is more than 0.8, the path has a complete mediator effect.PLS was used to perform the SEM.Since the results

Mobility of cadmium
To study the retention of Cd in soil samples, the mobility of Cd in soil was calculated, which shows the relative retention time of Cd in the soil (Nemati et al., 2009).In our research, mobility was calculated using Eq. 3.
where C f1+f2+f3 is the sum of the values of Cd extracted in the first three steps of the sequential extraction methods and C f4 is the concentration in the residual fraction.

Enrichment factor (EF)
Enrichment factor is an assessment of the possible impact of anthropogenic activities on the content of heavy metals in the soil environment.To identify the impact of anthropogenesis on the heavy metal content in the soil, the concentration of heavy metals characterized by low variability of occurrence was used as a reference.Reference elements are usually Fe and Al (Sutherland, 2000).EF is calculated using Eq. ( 4): Classification of ER is shown in Table 3 (3)

Geo-accumulation index (I geo )
In 1969, Müller defined an index of geo-accumulation (I geo ) to determine and define metal contamination in soil by comparing current concentrations referenced to the background natural levels of the elements.Equation 5 can be used to calculate contamination (Srinivasa Gowd et al., 2010;Yaylali-Abanuz, 2011).Table 4 shows the classification of I geo .
C n = Cd concentration in the soil sample, B n = Cd concentration in soil control.In this equation, coefficient 1.5 is used to remove the effects of lithogenic factors on the control soil sample (Gonzales-Macias et al., 2006).

Contamination factor (CF)
To determine soil contamination by heavy metals, the contamination factor was used.Based on this factor, the concentration of heavy metals in soil was compared to its normal concentration to determine the degree of soil contamination (Facchinelli et al., 2001).This factor is calculated as shown in Eq. 6.The index that can be used to describe the heavy metal with the highest threat to the soil environment is the single contamination index, suggested by Hakanson (1980).
The contamination factor distinguishes four classes of quality for soil (Table 5).
This index represents the amount of available Cd out of the total Cd present in the soil, which can be absorbed by plants (Eq.7).The availability ratio is highly dependent on soil properties and is more sensitive to anthropogenic factors (Massas et al., 2010(Massas et al., , 2013)).
C ia = Available metal concentration in the ith sampling site, ( 5) Vol:. ( 1234567890) C it = Total metal concentration in the ith sampling site.

Statistical analysis
A global positioning system device (manufactured in Garmin Ltd.) was used to record the sampling sites' geographic features.SAS 9.1, Arc GIS 10.4,GS + , Surfer 8, and Excel software were used for performing statistical analysis, drawing geographical distribution maps, and drawing graphs of some soil parameters.The Kolmogorov-Smirnov (K-S) test was used to assess the normality of the data.Also, an independent sample t-test was used to compare the content of Cd of the farm's wheat with the control sites.

Phosphorus distribution
According to the results, the average content of available P in the study area was 89.57(mg kg −1 ) (Table 6).The minimum and the maximum values of available P were 25 (mg kg −1 ) and 500 (mg kg −1 ), respectively.The mean value of available P in the irrigated soils (129 mg kg −1 ) was higher than in the rainfed soils, with an average of 65 (mg kg −1 ).The mean value of total P was 1163 (mg kg −1 ) in the irrigated soils, which was higher than that of the rainfed ones (814 mg kg −1 ).Results demonstrated that P content has increased in agricultural lands more than in control ones.Once P enters the soil through chemical fertilizers (inorganic source), manure, biosolids, or dead plant or animal debris (organic sources), it cycles between several soil pools via processes, such as mineralization, immobilization, adsorption, precipitation, desorption, weathering, and dissolution.While weathering, dissolution, mineralization, and desorption increase available P in the soil for plant uptake, immobilization, adsorption, precipitation, runoff, and erosion decrease the available P. Organic matter is an important factor in controlling available P. With the addition of organic matter, availability of P increases.Manures are a source of inorganic and organic P. Organic P must be mineralized to orthophosphate to become available for the plant.Some manure, especially solid manures, have a low nitrogen-to-phosphoride (N/P) ratio relative to crop requirements, so the application of manure alone to meet the crop N requirement can lead to P build-up.The use of chemical fertilizers and animal manure is the most important factor in increasing P percentage in agricultural lands (Afyuni,2007;Basak, 2019;Omenda et al., 2021).In total, soil samples revealed no P concentration above the normal concentration of this element in the soil.According to the result, it has been shown that many samples had a P concentration near the critical range (50-150 mg kg −1 ).
Figure 2 shows the total and available P distribution maps in the Hamadan province.About 75% of the total P distribution was between 300 and 900 (mg kg −1 ) concentrations, which was mostly in the southern regions of the province (Fig. 2).Also, about 5% of the total P concentration was more than 1500 (mg kg −1 ), which was mostly in the southeastern regions of the province.According to the available P distribution, approximately 90% of the available Cd concentration was between 40 and 120 (mg kg −1 ), which was mostly in the central and southern regions of the province (Fig. 2).Furthermore, about 10% of the available P concentration was more than 150 (mg kg −1 ).This amount was mostly in the northeastern regions of the province.The results showed that the amount of P in the agricultural lands has increased.Phosphorus fertilizers have been found as one of the main factors in increasing P in agricultural lands (Dharma-Wardana, 2018;Rapheal et al., 2007).

Cadmium in the soil
The Cd concentration values for different land use soils are mentioned in Fig. 3.The mean value of available Cd in the study area was 0.155 (mg kg −1 ).The mean value of available Cd in the irrigated soils (0.180 mg kg −1 ) was higher than in the rainfed soils, with an average of 0.154 (mg kg −1 ).The average soil total Cd was 1.90, 2.22, and 1.3 (mg kg −1 ) in rainfed, irrigated, and control one, respectively.In this work, as shown in Fig. 3, soil samples in farms showed a higher concentration of Cd than the control soil samples.The data showed that many soil samples in the study area had Cd concentration near the critical range (3-8 mg kg −1 ).Various studies have stated that the threshold for Cd contamination in soil is 3 (mg kg −1 ) (Rodriguez-Flores & Rodriguez-Castellon, 1982;Cicek & Koparal, 2004).According to available scientific data, the difference between contaminated and non-contaminated soils in calcareous soils is 2 (mg kg −1 ) of total Cd (Wang, 1999).
The unbalanced use of chemical fertilizer is considered the main factor that enters heavy metals in agricultural lands.Cd in soils is derived from both natural and anthropogenic sources.Natural sources include underlying bedrock or transported parent material, such as glacial till and alluvium.Anthropogenic input of Cd to soils occurs by aerial deposition and sewage sludge, manure, and phosphate fertilizer application (Kabata-Pandyas and Mukherjee, 2007).Cd is much less mobile in soils than in air and water.The major factors governing Cd speciation, adsorption, and distribution in soils are pH, soluble organic matter content, hydrous metal oxide content, clay content and type, presence of organic and inorganic ligands, and competition from other metal ions (Arshad et al., 2016;Lamb et al., 2016).The use of Cd-containing fertilizers and sewage sludge is considered to be the primary reason for the increased Cd content of soils over the last 20 to 30 years in Europe (Jensen & Bro-Rasmussen, 1992).Atmospheric Cd emissions deposition onto soils has, in general, decreased significantly over that same period (Cook & Morrow, 1995;Mukunoki & Fujimoto, 1996;Yuan et al., 2019).Indeed, recent studies in Europe have demonstrated that atmospheric emissions do not have a significant impact on the Cd content of soils (Bak et al., 1997).The average natural abundance of Cd in the earth's crust has most often been reported from 0.1 to 0.5 mg kg −1 .Much higher and lower values have also been cited depending on many factors.Igneous and metamorphic rocks tend to show lower values, from 0.02 to 0.2 mg kg −1 , whereas sedimentary rocks have much higher values, from 0.1 to 25 ppm.Naturally, zinc, lead, and copper ores, mainly composed of sulfides and oxides, contain even higher levels, 200 to 14,000 mg kg −1 for zinc ores and around 500 mg kg −1 for typical lead and copper ores.The raw materials for iron and steel production contain approximately 0.1 to 5.0 mg kg −1 , while those for cement production contain about 2 mg kg −1 .Fossil fuels contain 0.5 to 1.5 ppm Cd, but phosphate fertilizers contain 10 to 200 mg kg −1 Cd (Cook & Morrow, 1995).

Factor loads
Factor loads resulting from the implementation of the SEM are demonstrated in Table 7.The loads are calculated by calculating the correlation between the structure's indexes and are equal to or greater than 0.4 (Hulland, 1990).Klein also stated that the factor load is between zero and one.The factor load of less than 0.3 shows that the relationship is weak and negligible.If this value is between 0.3 and 0.6, it is moderate, and if greater than 0.6, it is strong.Table 7 shows that Pb, in the rainfed and the chemical fertilizer used in the irrigated farms, has the most effective loads.

Evaluation of the SEM
The most usable criteria for the fitness of the SEM are used in this study.These criteria consist of significance factor (T-values), determination coefficient (R 2 ), and participating factor (Q 2 ).T-values are the primary criterion for evaluating the relationship between the structures in the SEM.When the absolute value of this parameter is equal to or greater than 1.96, the structure's relation is suitable, and the primary hypothesis (the effect of the model's parameters on the Pb durability) is confirmed with the reliability level of 95%.Table 8 shows the parameters related to T-value.This result demonstrates that most of the parameters (except sand and pH) have a meaningful effect on the Pb durability.R 2 is a criterion to connect the measurements and structural part of SEM.This parameter shows the effect of an exogenous variable (Cd) on an endogenous variable (effective parameter on Cd's durability).Error reduction in measuring models or an increase in the variance between the structure and the indices are the main merits of the PLS method.It should be noted that the R 2 value can be calculated just for the endogenous (dependent) model structures, which is equal to zero for exogenous structures.The range of R 2 is between zero and one, which shows the fitness of the SEM in three levels weak (0.19), moderate (0.33), and strong (0.67).Table 9 shows the results of R 2 in two studied statuses of this research.These results demonstrate that the R 2 value is moderate and strong in all the parameters except in sand and pH.
Q 2 is a criterion introduced by Geisser in (1975), which determines the model's forecasting potential.It is believed that models with acceptable fitness in their structural part should have the forecasting ability of endogenous structures' indices.It means that if the relationship between structures in a model is appropriately defined, structures can have a sufficient impact on each other's indices and approve the hypotheses.Q 2 values of 0.02, 0.15, and 0.35 indicate that the forecasting ability of the endogenous structures' indices is weak, moderate, and strong, respectively.If a structure's Q 2 value of an endogenous structure is equal to or less than zero, the relationship between the endogenous structure and other structures is not well defined, and the model needs some modifications.So generally, the Q 2 value is the criterion showing the model's forecasting ability at the weak, moderate, and strong levels.Table 10 demonstrates the model has a strong forecasting ability since the components' forecasting value is all greater than 0.35 (except for sand and pH).
Figures 4 and 5 show the structures' (parameters') relations on Cd's durability in two region types, rainfed and irrigated lands.In both rainfed and irrigated regions, the chemical fertilizer parameter (0.92 and 0.98) has the most effect on Cd.In rainfed regions, clay and rainfall also have an essential effect on Cd's durability in soil, while in irrigated regions, clay and calcium have the most effects after chemical fertilizers.Results also show that sand and pH have a negligible effect on Cd.
In both the soil types, sand and pH do not have an essential effect on soil's Cd.Results of the developed method also showed the negligibility of the effect of these two parameters.On the other hand, Ca and Pb are critical parameters due to their competition with Cd in surface absorption in the two soil types.CaCo 3 , OM, and clay also have a vital role in elements' durability due to having surface charge and absorption ability of elements like Cd.The allowable entry and accumulation level of heavy metals is dependent on cation exchange capacity (CEC) (CEC of a soil is the function of organic materials and clay).The amount of metals entering the soil increases with an increase in CEC (Küpper, 1999).
The researchers showed that increasing the CEC will increase the amount of heavy metal added to the soil in the surface unit.The CEC is one of the essential soil features in estimating environmental dangers resulting from heavy metal sand and some cationic organic pollutants.So that more CEC causes the reduction in the probability of contamination of underground and surface water with cationic pollutants.Rajaie et al. (2006) observed that adding Cd to the soil converted 82% clay loam soil and 88% sandy loam soil into three forms exchangeable, carbonate, and organic Cd.They believed that higher concentrations of Cd in two forms of exchangeable and carbonate in sandy loam soil indicated the higher usability of Cd in higher textured soils.Lower accessibility in clay loam soil is due to its higher CEC than sandy loam soil.Singh & Nayar (1993) reported that soil calcium carbonate is one of the most critical factors determining the surface absorption of metals.Calcite creates a strong bond with heavy metal ions, and it is probable to form stable octavite (CdCO 3 ) precipitate at pH > 7.8.Therefore, soils with high amounts of equivalent calcium carbonate can retain more cadmium and have higher absorption potential than soils with lower equivalent amounts of calcium carbonate.Ramachandran and Souza (1994) stated that octavite deposition (CdCO 3 ) on carbonates in high-pH soils or calcareous and alkaline soils is an acceptable reason for increasing cadmium absorption in these soils.Rajaie et al. (2006) mentioned that in their study, immediately after adding metal to the soil, the major part of cadmium converted to carbonate form.Based on this observation, they stated that calcium carbonate plays a prominent role in keeping cadmium in the calcareous soils with a high probability.Ahmad Bhat et al. (2014) reported that increasing calcium decreased cadmium absorption by the mustard plant.In this research, they showed the antagonistic effect of calcium on cadmium.Cadmium is an analog of calcium and is transported by the calcium transport systems of plant cells.The study also showed that the tonoplastic H + /Ca 2+ antiporter in Arabidopsis is involved in cadmium transport from the cytoplasm to the vacuole (Zorrig et al., 2012).Therefore, the amount of cadmium in the plant tissue depends on the amount of calcium in the root environment (Kurtyka et al., 2008).

Mobility of cadmium
The Cd mobility values for different land use soils are shown in Table 11.The mean value of mobility in the study area was 1.56, 1.48, and 0.42 for rainfed, irrigated, and control, respectively.According to the results in Table 6, since the mobility for Cd was higher than 1 in the rainfed and irrigated regions, the retention time of Cd in the soil was low.The mobility, immobility, and thus toxicity of heavy metals in soil depend primarily on their binding forms.The high amount of Cd associated with the non-residual fractions shows that Cd may be easily transferred into the food chain through water reservoirs and uptake by plants growing in the soils (Tokalioglu et al., 2003).A high contamination factor of Cd shows low retention time and high environmental risk.In this study, Cd is mainly associated with carbonate, organic, soluble, and exchangeable fractions, respectively.For that reason, it is precarious and mobile.

Enrichment factor
The enrichment ratio (EF) values in soils under different land-use types are shown in Fig. 6.The result indicated that ER in the study area was 7.6, 8.9, and 5 for the rainfed, irrigated, and control, respectively.According to the results in Table 3, since the EF for Cd in the rainfed and irrigated lands was between 5 and 10, these lands were placed in a high enrichment category based on the intensity of the enrichment   (2015) in Table 3.Also, this factor was at a normal level for the control land.The EF is one of the most common procedures to investigate human impact on soil.In other words, the EF shows the intensity of external factors on soil conditions (Yao et al., 2017).Also, this method is an appropriate technique to assess the source of soil pollution, including lithogenic and anthropogenic (Ademo et al., 2005).The concentration of an element in the soil sample is compared to the control sample to calculate this factor.According to Hernandez et al. (2003), an EF up to 1 indicates lithogenic sources, while an EF of more than one indicates that soil pollution has an anthropogenic source.Figure 6 represents the ER distribution in Hamadan province.
The highest amount of EF in the study area (about 30%) was between (1.5-2.17),mainly in the central regions of the province (Fig. 7), where there is high agricultural activity and population density.In total, the results showed that the amount of EF in the agricultural lands has increased, and lands were enriched in Cd due to the increased amount of phosphorus concentration in the agricultural lands, which can be attributed to the imbalanced use of phosphorus fertilizers during the past decade (Wei & Yang, 2010).
Geoaccumulation index (I geo ) The geoaccumulation index (I geo ) for the studied element in the soil is summarized in Fig. 8.The mean value of this index in the study area was 2.6, 2.9, and 2.1 for rainfed irrigated and control lands, respectively.This index was expressed by Muller for the first time, which was identified as the Muller index.
According to Table 4, a category in seven groups was introduced to the intensity of geoaccumulation index (Luoping et al., 2007;Muller, 1969).As Fig. 8 indicates, the I geo values for the rainfed, irrigated, and total lands were 2.6, 2.9, and 2.7, which were placed in the Moderate to strong level according to the category of I geo shown in Table 4.The I geo of Cd in both lands of wheat farming showed that the soils were more polluted than the control land.This result could be attributed to human activities such as agricultural activities that enter heavy metals into the soil (Luo et al., 2007).The I geo distribution map in the studied farms is indicated in Fig. 9, which shows the same trend as EF distribution.The highest amount of the I geo in the study area (About 60%) was between (2.67-3.27),which was mainly in the central and southern regions of the Hamadan province, including Kabudarahang, Ghahavand, Malayer, and Nahavand cities, according to Fig. 9, where the most agricultural lands are located.Also, the results revealed that all studied areas, except for the background location, had I geo values greater than 1.Based on the values of I geo , the agricultural lands were found uncontaminated to moderately enriched with Cd.In the future, it will increase due to the continuous entry of Cd in various ways, particularly in agricultural activities (Esmaeili et al., 2014).In a study conducted by Rodriguez Martin et al. (2006) on the concentration of heavy metals in the agricultural soils in Spain, it was revealed that Cr and Ni are controlled by parent materials, and Cd, Pb, Hg, Cu, and Zn are affected by human activities.Shirani et al. (2020) also obtained an I geo map of Jazmourian sediments in southeastern Iran.
Contamination factor (CF) The contamination factor can be used to show the environmental contamination related to a specific element (Abrahim & Parker, 2008).The Cd contamination factor amounts are shown in Fig. 10 for different land use of soils.The mean value of this index in the study area was 1.46 and 1.7 for rainfed and irrigated lands.The contamination factor indicates the amount of soil contamination by heavy metals.This factor is obtained by dividing the concentration of the element in the soil sample by the concentration of the same element in the soil background sample (Abrahim & Parker, 2008).According to Hakanson's studies, Table 5 introduces a category for the intensity of the contamination factor (Hakanson et al., 1980).
The results showed that the values of CF were high in the rainfed and irrigated farming and that the values for both lands were in the medium class according to the category of CF indicated in Table 5.The results showed that the amount of Cd in the agricultural lands has increased and can enter the human body by consuming the plants that grow on these lands.The distribution map of the CF in studied farms is shown in Fig. 11.The CI values in the study area were between (0.3-2.22); the highest values were mainly in the central regions of the Hamadan province, including the Kabudarahang and Ghahavand cities, according to Fig. 11, where the agricultural activities and population are intense as mentioned in the previous section.
Availability ratio (AR) Figure 12 shows the Cd availability ratio (AR) values in the study area.The mean value of AR in the different parts was 8, 8.2, and 6.8 for the rainfed, irrigated, and control land, respectively.According to these results, the AR for Cd in the rainfed and irrigated land was higher than in the control one.This index expresses the value of available Cd out of total Cd present in the soil, which plants can absorb, and is highly dependent on soil properties,  Strongly to extremely strongly > 5 Extremely polluted including organic matter, clay content, and soil pH.Also, decreased effect of lithogenic factors makes it more sensitive to anthropogenic factors (Massas et al., 2013).Therefore, there was an increasing AR in the rainfed and irrigated land, and the main reason for this can be attributed to human activities such as the widespread use of chemical fertilizers that contain Cd impurity, especially phosphors.The results showed that the amount of Cd in the agricultural lands has increased and can enter the human body by consuming plants that grow on these lands.Figure 13 illustrates the AR distribution in the study area.As the map shows, the central and eastern regions of the Hamadan province, including Razan, Nahavand, Hamadan, and Nahavand cities,  have the highest amount of AR (About 60%), which were between 8.8-13.8.Also, the results showed that the amount of AR in the agricultural lands is slightly high.According to Massas et al. (2013), the high availability of metals may indicate a relatively recent enrichment of soil with metals that have not yet been sequestered and heavily absorbed by soil colloids.The availability of metals depends on the fraction of free metals in the soil solution concerning the total metal content in the solid phase (Takac et al., 2009).

Conclusion
Calculating contamination indices characterized by different features determines the proper theoretical basis for the appropriate interpretation of  Author's Contribution MR, EE, and GR conceived of the presented idea.GR, TK, and EE developed the theoretical framework.MR, EE, and ECAA developed the theory and performed the computations.GR, TK, and EE verified the analytical methods.MR, SN, and ECAA carried out the experiments.All authors discussed the results and contributed to the final manuscript.
Funding None.

Availability of data and materials
Yes.

Declarations
Competing interests The authors declare no competing interests.

Ethical approval
The subject of plagiarism has been considered by the authors, and this article is without problem.
Consent to participate None.
Consent to publish Yes.

Fig. 1
Fig. 1 Geographical location and land use of the Hamadan province and sampling points ◂

Fig. 2 Fig. 3
Fig. 2 Distribution map of available and total P in the study area

Fig. 4 Fig. 5
Fig. 4 Relation between the model's parameters and the Cd's durability in the rainfed regions

Fig. 6
Fig. 6 Mean value of EF in the study area

Fig. 7
Fig. 7 Distribution map of enrichment factor (EF) in the study area

Fig. 8
Fig. 8 Mean value of I geo in the study

FigFig. 10
Fig. 9 Distribution map of geoaccumulation index (I geo ) in the study area

Fig. 11 Fig. 12
Fig. 11 Distribution map of contamination index (CF) in the study area

Table 3
(Diop et al., 2015)F based on the obtained value(Diop et al., 2015) category introduced by Diop et al.

Table 7
Factor loads' coefficients of evaluated parameters in different parameters

Table 8 T
-value test results, the effect of different parameters in the model on Cd's durability

Table 9
The coefficient of R 2 index for endogenous variables of the model in the studied region

Table 10
Coefficient of Q 2 index for forecasting model in the two studied regions