周蓓蓓,李文倩,郭江,等. 安徽矾矿土壤重金属污染源解析模型对比与优选[J]. 农业工程学报,2024,40(3):321-327. DOI: 10.11975/j.issn.1002-6819.202309008
    引用本文: 周蓓蓓,李文倩,郭江,等. 安徽矾矿土壤重金属污染源解析模型对比与优选[J]. 农业工程学报,2024,40(3):321-327. DOI: 10.11975/j.issn.1002-6819.202309008
    ZHOU Beibei, LI Wenqian, GUO Jiang, et al. Comparison and preference of source analysis models for heavy metal contamination of soil from alum mines in Anhui Province, China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(3): 321-327. DOI: 10.11975/j.issn.1002-6819.202309008
    Citation: ZHOU Beibei, LI Wenqian, GUO Jiang, et al. Comparison and preference of source analysis models for heavy metal contamination of soil from alum mines in Anhui Province, China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(3): 321-327. DOI: 10.11975/j.issn.1002-6819.202309008

    安徽矾矿土壤重金属污染源解析模型对比与优选

    Comparison and preference of source analysis models for heavy metal contamination of soil from alum mines in Anhui Province, China

    • 摘要: 矿区资源开采导致土壤污染日益严重,直接影响周边土壤、水体环境的稳定性,精准预测重金属污染源解析对矿山修复、治理具有重要指导作用。在前期研究基础上,为提升土壤介质模型的解释度,进一步选取了土壤重金属源解析评价中成熟度高且精准性好的正定矩阵因子分析法positive matrix factorization, PMF)及绝对因子分析-多元线性回归(absolute factor analysis - multiple linear regression, APCS-MLR)模型,以充实前期UNMIX多元受体模型分析矾矿土壤重金属污染来源及源贡献率的结果,结合生态风险评价方法,对比定量条件下最适宜解析研究区域源的模型。结果表明:1)生态高风险区域主要集中在研究区南部和东部,Cd是矿山主要风险元素,地累积指数(index of geoaccumulation)均值3.75与潜在生态风险指数(potential ecological risk index)均值731.22解析结果高度一致,但潜在生态危害指数的结果综合性更好。2)对比3种模型的污染源解析结果,PMF模型解析出4个污染源:分别为燃煤源、自然-交通综合源、自然源和大气沉降源,源贡献率分别为38.15%、20.62%、24.28%、16.95%。3)PMF模型的总体变量拟合优度R2达到了0.96,拟合效果最好。PMF模型模拟数据会集中采样点误差,确定最适污染源数目及相应污染物贡献率,使得源解析结果更精准,更适用于复杂的矿山污染土壤情况,符合实际研究情况。该研究结果可为后续矿区开采后污染土壤的修复治理工作提供溯源依据参考。

       

      Abstract: Soil pollution is becoming increasingly serious due to resource exploitation in mining areas, which directly affects the stability of the surrounding soil and water environment, and the accurate prediction of heavy metal pollution source analysis has an important guiding role in scientific mine remediation and treatment. On the basis of the previous study, in order to improve the interpretation of the soil media model, positive matrix factorization (PMF) and absolute factor analysis-multiple linear regression (APCS-MLR) models, which have a high degree of maturity and accuracy in the evaluation of heavy metal source analysis in soils, were further selected to enrich the UNMIX model in the previous study. The results of the multiple receptor models analyzing the sources of heavy metal contamination and the contribution of the sources were combined with the ecological risk assessment method to determine the most suitable model in study area under quantitative conditions. The results showed that: 1) the ecological high-risk areas were mainly concentrated in the south and east part of the study area, and Cd was the main risk element of the mine;the mean value of igeoaccumulation index was 3.75, which was highly consistant with the mean value of 731.22 for the potential ecological risk index though latter provided a more comprehensive evaluation of ecological hazards. 2) Comparing the results of the three models, the PMF model resolved four pollution sources: coal combustion source, natural-traffic integrated source, natural source and atmospheric deposition source, and the source contribution rates are 38.15%, 20.62%, 24.28% and 16.95%, respectively. 3) The fitted variables R2 in the PMF model reached to 0.96, which showed the best fitting effect. The PMF model refines source apportionment by accounting for sampling point errors and accurately ascertaining pollution sources and their contributions, making it highly suitable for complex mine-contaminated soils in realistic research settings. The findings of this study can provide a reference for tracing the origins of contaminants, which is essential for the remediation efforts of polluted soils following mining activities in the area.

       

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