Assessment of Pollution in the Central Soils of Khuzestan Province with Potentially Toxic Elements (PTEs) and their Origins

In recent years, soil contamination with potentially toxic elements (PTEs) has become a major problem in most parts of the world. PTEs are naturally generated from the pedogenesis in the soil and are formed mainly by rock weathering. Nevertheless, the natural content of metals, i.e., Cr, Zn, Ni, Pb, Cd, used to be low in the soil, but due to anthropogenic activities such as industrial emissions, atmospheric transportation, sewage irrigation, and application of pesticides and fertilizers, there is an increase in the content of PTEs. PTEs in soil are one of the most important environmental pollutants due to their toxicity, durability, easy absorption by plants and long half-life. Therefore, the assessment of soil health is very important for the sustainable development of agriculture and the rehabilitation of soils contaminated with PTEs. The present study was conducted to quantify PTEs pollution for soil environmental assessment using a flexible approach based on multivariate analysis and using pollution indicators in a part of the central lands of Khuzestan province.
 
For this purpose, in February 2021, 200 surface soil samples (0-10 cm) were taken using stratified random sampling. The collected soil samples were cleaned by removing plant materials and other pebbles, and air dried, powdered, and sieved by using a 2 mm sieve size. The interest in soil's physical and chemical properties i.e., pH was determined with a digital pH meter. Soil textural particles were measured by the hydrometer method, soil organic carbon (SOC) content was estimated by following Walkley and Black method, bulk density (BD) was measured by the Clod method, and total metal content was determined using the aqua-regia solution digestion method and analyzed using Inductively Coupled Plasma-Optical Emission spectrometry (ICP-OEC). The level of Pb, Ni, Zn, Cr pollution was estimated based on environmental indicators including contamination factor (CF), enrichment factor (EF), geo-accumulation index (Igeo), pollution index of individual metals (PI), and modified pollution index of individual metals (MPI). Multivariate statistical methods including correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to find the source of metals in the soil. All statistical methods were performed using SPSS (26 version) software.
 
Measurement of soil pH showed that the soil of the studied area tends to alkalinity. Also, the soil texture in this area is loam. The results showed that the SOC in these soil samples is 0.71%, and the range of EC (between 0.18 and 60.5 dS/m) indicates the distribution of saline and non-saline soils in the studied area. The total average concentration of Zn, Ni, Cr, and Pb were 60.26, 50.96, 50.38, and 12.67 mg/kg, respectively. The order of average for heavy metals was Zn> Ni> Cr> Pb. The highest amount of standard deviation and concentration changes were observed in Zn and Pb elements. These two elements also showed a high degree of variation coefficient in the studied area, which can indicate the high impact of human activities on the content of these elements. The results obtained from the application of multivariate statistics showed that there is a positive correlation between the elements such as Zn, Ni, and Pb in the study area, indicating that these metals probably have the same source. Whereas the absence of correlation of Cr with these elements indicates a separate source for this element compared to Pb, Zn, and Ni. There was also a strong relationship among these elements based on the PCA and CA classification. Based on the multivariate statistical analysis the source of pollution for the metals studied was mainly from both anthropogenic and geogenic activities. The results showed that the soil samples taken from the study area are in the low pollution category based on the individual element indices of CF and Igeo, but in the moderate pollution class based on the EF index. In addition, the evaluation based on the cumulative and multi-element indices of PI and MPI showed that 100% of samples have high pollution.
 
The present study concludes that the average values of Zn, Ni, Cr, and Pb were found to be below the guidelines set by the IEPA (Iran Environmental Protection Agency) as well as the Earth's crust values. The results indicate existing relationships among the studied variables, revealing that the heavy metals Zn, Ni, and Zn share the same source in the study area. Additionally, it was observed that the source of Cr is primarily geogenic in nature. These findings highlight the significance of utilizing multivariate statistical methods and pollution indicators in tandem, as they prove to be valuable tools for evaluating and quantitatively determining the potential pollution risk.