生态环境学报 ›› 2026, Vol. 35 ›› Issue (10): 1611-1625.DOI: 10.16258/j.cnki.1674-5906.2026.10.011

• 研究论文【环境科学】 • 上一篇    下一篇

皖南地质高背景区富硒土壤重金属污染源解析与风险评价

谢国梁1(), 段颖2, 丁丹3, 孙玉永1, 徐新宇1, 袁静1   

  1. 1 铜陵学院智能建造与空间信息学院, 安徽 铜陵 244061
    2 包头市高新区资源环境局, 内蒙古 包头 014060
    3 安徽省地质矿产勘查局321地质队, 安徽 铜陵 244033
  • 收稿日期:2025-11-17 修回日期:2026-08-26 接受日期:2026-09-07 出版日期:2026-10-18 发布日期:2026-10-21
  • 作者简介:谢国梁(1988年生),男,副教授,博士,从事黑色页岩风化环境效应研究。E-mail: 010032@tlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(42207293);安徽省自然科学基金项目(2208085QD110);安徽省高校理工科教师赴企业挂职实践计划项目(2024jsqygz103);安徽省优秀青年教师培育项目(YQYB2024072);安徽省教育厅科学研究重点项目(2025AHGXZK31360)

Source Apportionment and Risk Assessment of Heavy Metals in Selenium-Rich Soils in the High Geochemical Background Area of Southern Anhui Province

Xie Guoliang1(), Duan Ying2, Ding Dan3, Sun Yuyong1, Xu Xinyu1, Yuan Jing1   

  1. 1 School of Intelligent Construction and Spatial Information, Tongling University, Tongling 244061, P. R. China
    2 Baotou Rare Earth High tech Zone Resources and Environment Bureau, Baotou 014060, P. R. China
    3 321 Geology Team, Bureau of Geology and Mineral Exploration of Anhui Province, Tongling 244033, P. R. China
  • Received:2025-11-17 Revised:2026-08-26 Accepted:2026-09-07 Online:2026-10-18 Published:2026-10-21

摘要:

【目的】以皖南地质高背景区富硒耕地为研究对象,对富硒土壤重金属来源、分布及其生态与健康风险进行评价,为制定有效的土壤污染治理策略提供科学依据。【方法】采集并分析了51份表层(0-20 cm)富硒耕地土壤样品中重金属As、Cd、Cr、Cu、Ni、Pb、Sb和Zn的质量分数,运用Pearson相关性分析、PMF和Monte Carlo模型,开展重金属来源解析、生态风险与人体健康风险评估。【结果】结果表明,1)8种重金属元素的平均质量分数均高于安徽省土壤背景值,其中Cd的变异系数最高,受人类活动影响显著。2)研究区重金属来源分为综合源(33.5%)、自然源(23.5%)、采矿源(18.1%)和农业源(24.6%)。3)基于PMF模型的“双重风险评价模型”显示,自然源和采矿源是潜在生态风险的主要贡献源,自然源和农业源是人群非致癌与致癌风险的主要贡献因素;Monte Carlo模型表明,土壤重金属对当地人群存在一定的非致癌与致癌健康风险,主要暴露途径为间接饮食摄入,As是最主要的风险元素。【结论】研究区富硒土壤存在多重来源的重金属累积,生态与健康风险贡献源存在差异,需制定分区分类管控措施。

关键词: 富硒土壤, 重金属, 源解析, PMF模型, Monte Carlo模型, 生态和健康风险评价, 皖南地质高背景区

Abstract:

[Objective] Identifying the sources, spatial distribution, and associated ecological and human health risks of heavy metals in selenium‑rich soils is critical for designing effective, evidence‑based pollution control policies. This study provides a comprehensive assessment of a high geochemical background area in Dongzhi‑Shitai County, southern Anhui Province, China, where naturally enriched selenium coexists with potentially toxic heavy elements. [Methods] Fifty-one cultivated topsoil samples (0-20 cm) were collected and analyzed for eight heavy metals (As, Cd, Cr, Cu, Ni, Pb, Sb, and Zn). A multi-method approach was applied, integrating Pearson correlation analysis, positive matrix factorization (PMF) receptor modeling, and Monte Carlo probabilistic risk assessment. Moreover, a novel PMF-based “dual risk assessment model” was employed to simultaneously evaluate potential ecological and human health risks. [Results] The results show that the concentration of eight heavy metals followed a consistent descending order: Zn > Cr > Cu > Ni > Pb > As > Sb > Cd. All eight metals exceeded the local geochemical background values for the Yangtze River-Huaihe River basin of Anhui Province, and notably high proportions of samples exceeded China’s risk screening thresholds for agricultural land: 78.43% for Cd, 29.41% for Cu, and 17.65% for As. Cd exhibited a particularly high coefficient of variation (124%), indicating substantial anthropogenic influence. Spatial analysis revealed two distinct distribution patterns, each associated with specific sources. Heavy metals such as Cd, Cr, Sb, and Zn exhibited similar high-value zones, spatially aligned with areas of Cambrian black shale distribution, including stone coal, indicating intense natural weathering as the dominant control. In contrast, elevated Cu, Ni, and Pb concentrations were observed in the northeastern and southwestern parts of the study area, where numerous large-scale metal smelting plants operate, indicating a strong industrial emission signature. Notably, forested areas overlapping with tea plantations and underlain by black shale also exhibited elevated metal levels, demonstrating that natural geogenic enrichment is not inherently benign. Statistical analyses confirmed that strong positive correlations (r > 0.75, p < 0.01) between Cr and Cd and between As and Sb indicated common origins, moderate correlations (r = 0.4-0.5) among As, Cd, Cr, and Cu suggested mixed influences; and weak correlations of As with Ni and Pb suggested distinct sources. Quantitative source apportionment using the PMF model identified four primary contributors: a composite industrial-transportation source (33.46%), natural weathering of black shale and stone coal (23.86%), mining operations (18.13%), and agricultural practices (24.55%). The composite industrial-transportation source dominated Zn (57.7%), Pb (56.1%), Ni (52.9%), and Cr (47.7%); natural weathering accounted for the majority of Sb (69.1%) and a substantial portion of As (39.8%); mining was the principal source of Cd (61.7%); and agriculture activities contributed most strongly to Cu (46.7%) and As (41.3%). A novel PMF-based “dual risk assessment model” was applied to evaluate potential ecological and human health risk, revealing significant differences between the two types of risk. Natural weathering and mining activities were the dominate drivers of ecological risk. The core black shale and stone coal outcrop area reached high-risk status (RE > 600) owing to intense geogenic release, with secondary enrichment in surrounding areas occurring through atmospheric dust deposition and surface runoff. In contrast, human health risks, including both non-carcinogenic and carcinogenic risks, were primarily attributable to natural and agricultural sources. The calculated non-carcinogenic and carcinogenic risks were significantly higher in children than in adults, highlighting children as a particularly vulnerable population. Probabilistic Monte Carlo health risk assessment confirmed that soil heavy metals pose certain non-carcinogenic and carcinogenic risks to local residents, with dietary intake as the predominant exposure pathway. Among all elements, As emerged as the most critical risk factor, making it the priority pollutant for control. Because the dominant sources differ between ecological and health risks, differentiated management strategies are warranted. In mining-impacted zones, an ecological-risk-priority strategy should be implemented, focusing on engineering controls such as anti-seepage measures at tailings ponds and slag storage sites to minimize Cd migration and release, restricting the use of highly high-As pesticides, and promoting green agricultural technologies. Given that dietary intake is the dominant exposure pathway, land-use planning and crop selection are critical. For example, planting low-As-accumulating crops in high-risk areas can effectively interrupt the exposure pathway. Children’s greater physiological susceptibility requires stricter pollution control and targeted risk mitigation in child-centric environments such as schools, playgrounds, and residential neighborhoods. Globally, although natural weathering is recognized as the main driver of heavy metal enrichment in black shale-derived soils, southern Anhui Province is distinctive because of its associated selenium-rich geological background, which generates a unique combined pollution pattern of “natural sources plus agricultural sources.” These characteristics impose stringent requirements on risk governance. First, the development of “selenium-rich” agricultural products requires greater caution to ensure that economic incentives do not undermine long-term ecological safety. Second, region-specific control strategies are essential. For example, in agricultural areas underlain by black shale, the focus should shift toward reducing reliance on chemical fertilizers and pesticides, standardizing agricultural waste management, and controlling heavy metal inputs at the source. Third, As, rather than Cd alone, should be identified as the priority control element in soil remediation strategies, given its widespread high health risk in black shale-derived soils. A comprehensive management strategy combining land-use planning, cropping system optimization (e.g., planting low-As-accumulating crops), and in situ remediation techniques is necessary to minimize human exposure to this element. Finally, this study identifies critical knowledge gaps. In particular, the biogeochemical cycling of heavy metals in Se-enriched soil systems remains poorly understood, especially the interactions between Se and chemically similar toxic elements such as As. Long-term studies tracking the health effects of actual dietary intake of produce grown in such soils are therefore urgently required. [Conclusion] A methodological framework integrating PMF, dual risk assessment, and Monte Carlo analysis, applicable to high geochemical background regions was proposed in this study. In Se-rich black-shale-exposed areas, natural heavy metal enrichment cannot be overlooked; agricultural activities are not innocuous and can exacerbate risks; As must be prioritized as the key control element; and children’s exposure requires targeted, source-aware interventions. In summary, this study provides a scientific basis for precise source apportionment of heavy metal pollution in selenium-rich soils in high geochemical background areas and for the implementation of priority control strategies.

Key words: selenium-rich soil, heavy metals, source apportionment, PMF models, Monte Carlo models, ecological and health risk assessment, high geochemical background area of southern Anhui Province

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