Guangxi boasts an abundant supply of manganese ore resources, with its annual output constituting approximately 30% of the national total. The distribution is extensive, encompassing manganese ore deposits in all 14 prefecture-level cities. Nevertheless, while endowed with rich manganese ore resources, the ecological and environmental issues resulting from manganese mining have grown increasingly severe, particularly the presence of excessive heavy metals in the surrounding farmland soil of manganese mining areas. According to relevant statistics, the area of farmland influenced by manganese mining within Guangxi amounts to approximately 13.32% of the total farmland area in the region. The contents of heavy metal elements, such as Cd and As, in the soil significantly exceed the average levels of soil in Guangxi. Relevant research indicates that in most edible parts of crops grown in farmland surrounding manganese mining areas, five types of heavy metals have surpassed the national food safety thresholds. These crops, containing excessive heavy metals, will ultimately accumulate in the human body through the food chain, causing irreversible harm to human health with long-term consumption.
However, to date, no research has been so far conducted on heavy metal pollution in farmland soil associated with manganese mining in Guangxi. Hence, to investigate the ecological risks posed by manganese mining to the surrounding farmland, the soil from farmland adjacent to the weathered manganese mining area in a typical karst region of Guangxi was selected as the research subject. Soil samples were collected from the 0 to 20 cm soil layer of farmland surrounding the manganese mining area, and the contents of eight heavy metal elements were analyzed. The potential pollution index method and the geoaccumulation index method were employed to assess the ecological risk of the farmland soil in the study area. Principal Component Analysis (PCA) and the Absolute Factor Score-Multiple Linear Regression model (ACPS-MLR) were utilized to qualitatively and quantitatively analyze the sources of heavy metals in the soil, while the Positive Matrix Factorization (PMF) model was applied to verify the results.
The findings reveal that the potential pollution risk of the farmland soil in the study area is moderate (RI = 222.28), among which the pollution indices of single indicators Cd ( Ei= 90.05) and Hg ( Ei= 89.6) reach the medium to severe level. The degree of geoaccumulation pollution follows the order: Cd > Hg > Zn > Pb > Ni > Cr > Cu > As. The evaluation results disclose that there exists a certain degree of pollution in the soil of the study area, mainly manifested by heavy metal elements such as Cd, Hg, As, Pb and Zn. The PCA results suggest that the farmland soil in the study area is primarily influenced by two pollution sources, which are likely human mining and emission sources and natural sources, contributing 61.8% and 26.2%, respectively. The quantitative analysis results of the ACPS-MLR demonstrate that Cd, Cr, Hg, Mn and Ni are mainly affected by human mining activities, contributing 97.22%, 81.79%, 92.47%, 97.28% and 82.81%, respectively. In contrast, As, Pb, and Zn are mainly influenced by natural sources, contributing 60.71%, 88.97% and 72.14%, respectively. Cu is mainly affected by the superposition of human mining activities and natural sources, contributing 47.75% and 52.25%, respectively. The verification results of the PMF indicate that the two models exhibit a high degree of similarity in identifying pollution sources. However, due to the significant differences in their mechanisms, discrepancies arise in the analysis of the contribution rates of pollution sources. Nevertheless, the two models together form a robust method verification system. A comprehensive consideration of both models can provide a more scientifically sound theoretical basis for pollution source tracing. Based on this study, the findings can serve as a foundation for the remediation of heavy metals in farmland soil and for the prevention and control of ecological risks in the study area.
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