Source identification and multi-index evaluation of heavy metal contamination in surface soils of the Pakal sub-watershed, Shazand

Extended Abstract
Introduction
Heavy metal contamination in terrestrial ecosystems has become a major environmental and public health concern worldwide, particularly in regions exposed to intensive industrial operations, agricultural inputs, and land-use alterations. Soil acts as both a reservoir and a medium for the transport of potentially toxic elements (PTEs), and therefore the evaluation of its contamination status is essential for sustainable land management and ecosystem protection. The Shazand region in Markazi Province, central Iran, hosts several heavy industries—including the Imam Khomeini Oil Refinery, a petrochemical complex, a large thermal power plant, and numerous mining activities, which have previously been reported as major pollution sources. Nevertheless, earlier investigations have predominantly focused on downstream plains and industrial zones, with limited knowledge regarding the contamination status of upstream sub-watersheds that are assumed to be less affected by anthropogenic pressures. The present study aims to fill this critical gap by providing a multi-index assessment of heavy metal contamination in the upstream Pakal sub-watershed in Shazand County, with an emphasis on how different land-use types (rangeland, cultivation, and orchards) influence the distribution, enrichment, and ecological risks of seven key heavy metals: Pb, Cd, Cu, Zn, Ni, Mn, and Fe.
 
Materials and Methods
A total of 32 composite soil samples were collected from surface layers (0–30 cm), following a systematic sampling design based on land units that integrated slope, land use, and lithology. The fine fraction (<0.063 mm) of the soils was analyzed using a near-total four-acid digestion method, and metal concentrations were determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS), ensuring high analytical accuracy for trace and ultra-trace elements. To comprehensively evaluate contamination status, multiple geochemical and ecological indices, including the Contamination Factor (CF), Degree of Contamination (Cd), Modified Degree of Contamination (mCd), Pollution Load Index (PLI), Geo-accumulation Index (Igeo), Enrichment Factor (EF), and Potential Ecological Risk (Eri and RI)—were employed. Moreover, multivariate statistical analyses, including Principal Component Analysis (PCA) with Varimax rotation and Hierarchical Cluster Analysis (HCA), were conducted to distinguish between natural (geogenic) and anthropogenic sources.
 
Results and Discussion
The results of one-way ANOVA indicated that none of the measured heavy metals exhibited statistically significant differences among the three land-use categories (P > 0.05), suggesting that spatial variation is primarily governed by natural geochemical controls rather than recent anthropogenic inputs. This finding was strongly supported by PCA and HCA. PCA extracted three principal components that together explained 69.59% of the total variance. The second component, dominated by Fe and Mn with extremely high loadings, clearly represented geogenic contributions associated with parent material and mineralogical composition. In contrast, the first component (characterized by Cd, Cu, and Pb) and the third component (Zn, Ni, and Fe) reflected mixed or anthropogenic influences, likely originating from agricultural activities such as phosphate fertilizers, pesticides, and machinery emissions. HCA further confirmed these groupings by separating the elements into two distinct clusters: a geogenic cluster (Fe and Mn) and an anthropogenic/mixed cluster (Pb, Cd, Cu, Zn, and Ni).
Despite the statistical homogeneity implied by ANOVA, contamination indices revealed noteworthy evidence of cumulative anthropogenic enrichment. CF values showed that Pb, Cu, Zn, Ni, Mn, and Fe had moderate contamination levels (CF > 1) across most land uses. Pb exhibited the highest CF value, particularly in agricultural soils (2.31), highlighting its elevated sensitivity to anthropogenic activities. Cadmium, although present in low absolute concentrations, demonstrated substantial ecological importance due to its high toxic response factor. The Degree of Contamination (Cd) ranged from 7.93 to 9.77, classifying all land uses as moderately contaminated. Notably, the Pollution Load Index exceeded unity for rangeland (1.05) and cultivated land (1.15), indicating cumulative pollution, while orchards (0.94) remained below the contamination threshold. This discrepancy between ANOVA and PLI highlights that while spatial variation is not statistically significant, long-term pollutant accumulation has occurred.
Geochemical indices further corroborated the dominance of natural sources. EF values for most metals fell within the “no enrichment” to “minor enrichment” categories (EF ≤ 3), confirming minimal anthropogenic addition. Only Pb showed consistent minor enrichment across land uses, particularly in orchards and agricultural soils, aligning with patterns typically associated with the historical deposition of lead-containing particulates and agrochemical inputs. Similarly, Igeo values for all metals, except Pb, were negative, indicating unpolluted conditions. Pb in cultivation and orchard soils was classified as “unpolluted to moderately polluted” (0 < Igeo ≤ 1), marking it as the only element with a detectable anthropogenic signal.
Ecological risk assessment showed that individual ecological risk values (Eri) for all metals fell within the low-risk category. However, Cd accounted for the highest proportion of ecological risk due to its high toxicity, despite its relatively low concentration. The integrated ecological risk index (RI) ranged from 32.30 to 44.08 for the three land uses—well below the threshold of 150—indicating a low overall ecological threat in the upstream Pakal sub-watershed.
 
Conclusions
In conclusion, although geogenic factors remain the primary determinant of heavy metal distribution in the upstream Pakal sub-watershed, pollution indices reveal subtle yet meaningful anthropogenic contributions, particularly from agricultural activities. The slight enrichment of Pb and Cu, the moderate contamination levels indicated by CF and Cd, and the PLI values exceeding unity in cultivated and rangeland soils collectively demonstrate the early stages of cumulative pollution in areas traditionally considered pristine. These findings underscore the necessity of continuous monitoring, stricter management of agricultural inputs, and preventive measures to mitigate further contamination and potential ecological risks. Given the proximity to major industrial sources and expanding agricultural practices, upstream sub-watersheds like Pakal serve as critical zones for early detection of contamination trends that may escalate if left unaddressed.