Department of Civil Engineering, Taiyuan University of Technology, Located at 79 West Yingze Street, Taiyuan, 030024, Shanxi, China.
Civil Engineering Disaster Prevention and Control Key Laboratory of Shanxi, Situated at 79 West Yingze Street, Taiyuan, 030024, Shanxi, China.
Environ Geochem Health. 2024 Nov 7;46(12):492. doi: 10.1007/s10653-024-02267-x.
In recent years, industrial waste and agrochemicals have reduced soil fertility and productivity, significantly impacting food security and ecosystems. In China, areas near red mud deposits from the aluminum industry show severe heavy metal contamination. This study examines agricultural soil near a red mud site in Shanxi Province, analyzing Cd, Cr, Hg, Ni, Pb, As, Cu, and Zn levels and distribution. Geostatistical methods and GIS are utilized to assess heavy metal pollution using the single factor index, the Nemerow integrated index, and the Hakanson potential ecological risk index. Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) and Positive Matrix Factorization (PMF) models are used for quantitative analysis of pollution sources. Research indicates that the average concentrations of eight heavy metals exceed the natural background values of Shanxi, placing them at a severe pollution level with moderate ecological risk. Specifically, indices for As, Pb, and Cr are 3.79, 3.38, and 3.26, indicating severe pollution; Cd, Cu, and Hg at 2.36, 2.62, and 3.00 suggest moderate pollution; Ni at 1.87 shows mild pollution, while Zn at 0.97 is not polluted. Hg presents the highest ecological risk with a coefficient of 120.00, followed by Cd (70.69) and As (37.92). Spatial analysis shows significant correlations among Pb, Zn, Cu, and Ni, while Cr, Cd, Hg, and As show greater variability and weaker correlations. Both models identify five main sources: industrial activities, agricultural fertilizers, red mud leachate, energy combustion, and natural geological backgrounds, with respective contribution rates in the APCS-MLR model at 27.7%, 24.6%, 18.1%, 15.2%, and 14.4%, and in the PMF model at 29.2%, 21.5%, 16.9%, 16.7%, and 15.7%. This study offers a scientific basis for controlling soil pollution in the region, filling a literature gap.
近年来，工业废物和农用化学品降低了土壤肥力和生产力，对粮食安全和生态系统产生了重大影响。在中国，铝工业赤泥沉积物附近地区显示出严重的重金属污染。本研究分析了山西省赤泥场地附近的农业土壤，测定了 Cd、Cr、Hg、Ni、Pb、As、Cu 和 Zn 的水平和分布。采用地统计方法和 GIS 技术，利用单因子指数、内梅罗综合指数和 Hakanson 潜在生态风险指数对重金属污染进行评价。采用绝对主成分得分-多元线性回归（APCS-MLR）和正定矩阵因子分解（PMF）模型对污染源进行定量分析。研究表明，8 种重金属的平均浓度超过山西的自然背景值，处于严重污染水平，具有中等生态风险。特别是 As、Pb 和 Cr 的指数分别为 3.79、3.38 和 3.26，表明污染严重；Cd、Cu 和 Hg 的指数分别为 2.36、2.62 和 3.00，表明中度污染；Ni 的指数为 1.87，表明轻度污染，而 Zn 的指数为 0.97，表明无污染。Hg 的生态风险系数最高，为 120.00，其次是 Cd（70.69）和 As（37.92）。空间分析表明，Pb、Zn、Cu 和 Ni 之间存在显著相关性，而 Cr、Cd、Hg 和 As 则具有更大的变异性和较弱的相关性。两种模型都识别出五个主要来源：工业活动、农业肥料、赤泥浸出液、能源燃烧和自然地质背景，在 APCS-MLR 模型中的贡献率分别为 27.7%、24.6%、18.1%、15.2%和 14.4%，在 PMF 模型中的贡献率分别为 29.2%、21.5%、16.9%、16.7%和 15.7%。本研究为该地区土壤污染控制提供了科学依据，填补了文献空白。
