Spatial distribution characteristics and source of heavy metals in abandoned mine soils in Ganzhou City
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摘要:
由于江西省赣南地区部分废弃矿山曾经存在无序开采和粗放经营现象，导致表层土壤和植被遭到破坏，造成尾矿堆积、水土流失、土壤酸化等问题，进而引发了区域性的环境污染。为深入了解赣南地区废弃矿山污染问题，以赣州市废弃矿山为研究对象，探讨矿山土壤重金属的空间分布特征及来源，对0~20 cm表层土壤样品的重金属含量进行测定, 综合运用多元统计分析、地统计学和GIS技术相结合的方法，分析土壤重金属的空间分布规律，同时运用主成分分析法查找矿区土壤重金属的形成原因。结果表明: ①废弃矿山土壤重金属含量较高，均值超过江西省背景值，其中金属矿的土壤重金属含量均值总体偏高，建材及砖瓦黏土矿总体偏低，矿山土壤重金属空间自相关Moran's I指数均大于0，在赣州市具有一定的空间正相关分布；②废弃矿山土壤重金属含量空间分布格局总体呈从西向东逐渐减小的趋势，根据普通克里金插值法预测得到的土壤重金属含量空间分布情况与局部空间自相关性分布情况结果基本一致; ③采用主成分分析法对废弃矿山土壤中的污染物来源进行解析, 两个主成分的方差贡献率分别为28.427%和20.370%，Cu和Zn含量的相关系数为0.330，可能具有同源或复合污染关系，Cu、Zn、As是矿区土壤污染物的主要组成部分，矿区土壤中Pb的吸附、迁移与土壤pH值关系密切。研究结果可为赣州市土壤污染防治和生态环境保护提供理论参考。
Abstract:The surface soil and vegetation in the southern Jiangxi Province have been severely damaged due to unregulated mining and extensive management practices in abandoned mines. This issue has resulted in accumulation of tailings, soil erosion, and soil acidification, which ultimately leading to regional environmental pollution. In order to gain a comprehensive understanding of the pollution problems in the abandoned mines of the southern Jiangxi Province, the authors in this paper took the abandoned mines in Ganzhou City as the research subject to explore the spatial distribution characteristics and sources of heavy metals in the mine soil. The content of heavy metal elements in surface soil samples (0~20 cm) was measured and the combined approach integrating multivariate statistical analysis, geostatistics, and GIS technology was employed to analyze the spatial distribution patterns of the heavy metals. Besides, the principal component analysis method was used to identify the factors contributing to heavy metal contamination in the mine soil. The research findings are as follows. ① The heavy metal content in the abandaned mine soils is relatively high, with the average value exceeding the background level of Jiangxi Province. Specifically, the average heavy metal content in the soil of metal mines is generally higher, while that content of building material and brick-tile clay mines is generally lower. The spatial autocorrelation Moran's I of heavy metals in the mine soil is consistently greater than 0, indicating a certain positive spatial correlation distribution within Ganzhou City. ② The overall spatial distribution pattern of heavy metals in the mine soil exhibits a decreasing trend from west to east. The spatial distribution of heavy metals in the soil, as predicted by ordinary kriging interpolation, is generally consistent with the results of the local spatial Moran's I distribution. ③ Through principal component analysis of pollutant sources in the abandoned mine soils, the variance contribution rates of the two principal components are 28.427% and 20.370%, respectively. The correlation coefficient between Cu and Zn content is 0.330, suggesting a possible common origin or combined pollution relationship. Cu, Zn, and As are the main components of soil pollutants in the mining area. Moreover, the adsorption and migration of Pb in the mining area soil are positively correlated with the soil pH value. The results of this research could provide valuable theoretical references for soil pollution prevention and control as well as ecological environment protection in Ganzhou City.
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表 1 研究区土壤重金属含量统计
Table 1. Statistical results of heavy metal content in soil of the study area
指标 含量/10-6 标准差 变异系数/% 偏度 峰度 PK-S 江西省背景值[15] 最小值 最大值 pH值 2.37 6.85 0.71 15.51 0.70 1.02 0.080 - Cu 1.06 350.94 53.68 178.84 5.16 27.28 0.086 20.30 Pb 5.63 459.53 98.78 98.04 2.25 4.72 0.070 32.30 Zn 11.96 355.36 51.03 61.97 3.22 13.26 0.074 69.40 Cr 0.31 271.72 58.11 114.89 1.98 4.08 0.068 45.90 As 0.01 564.27 41.80 325.40 9.51 106.79 0.068 14.90 注: pH值无量纲; “-”为无数据。 
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表 2 不同矿类及矿种的土壤重金属均值特征
Table 2. Average content of heavy metals in soil of different mineral categories and ore types
矿类 矿种 pH值 含量/10-6 Cu Pb Zn Cr As 金属矿 金 4.46 350.94 36.93 147.40 62.74 163.24 锰 4.55 49.66 38.75 98.78 203.11 43.73 钼 5.64 17.10 138.41 91.38 19.20 8.91 铁 5.19 29.86 459.53 271.99 53.68 16.83 钨 5.66 156.14 98.42 129.72 68.81 50.15 锡 6.15 184.10 42.41 202.73 70.89 564.27 其他金属矿 萤石 6.85 40.11 29.66 53.95 116.87 11.24 稀有金属矿 稀土 4.57 20.83 109.27 80.09 44.40 6.39 能源矿 煤 4.37 31.97 34.02 63.81 89.94 19.06 建材及砖瓦黏土矿 高岭土 4.70 8.63 81.59 97.40 6.90 1.37 石灰岩 3.59 27.34 36.16 34.02 78.32 10.34 碳质页岩 3.90 37.46 41.10 75.03 82.40 48.94 页岩 4.11 25.72 35.48 71.59 55.66 10.71 砖瓦黏土 4.70 24.17 26.26 68.10 95.50 36.38
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表 3 研究区土壤重金属含量全局自相关分析
Table 3. Global Moran's I analysis results of heavy metal content in soil of the study area
指标 Moran's I指数 Z值 P值 pH值 0.23 4.94 0.000 Cu含量 0.27 5.93 0.000 Pb含量 0.62 13.41 0.000 Zn含量 0.13 2.86 0.004 Cr含量 0.15 3.18 0.001 As含量 0.39 9.08 0.000
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表 4 KMO值和巴特利特检验结果
Table 4. Results of KMO and Bartlett tests
KMO值 巴特利特检验 近似卡方 自由度 显著性 0.612 287.209 15.000 0
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表 5 土壤重金属含量相关性系数矩阵
Table 5. Correlation coefficient matrix of heavy metal content in soil
指标 pH值 Cu含量 Pb含量 Zn含量 Cr含量 As含量 pH值 1 Cu含量 0.273** 1 Pb含量 0.109** 0.041 1 Zn含量 0.110** 0.330** -0.048 1 Cr含量 0.111** 0.140** -0.119** 0.127** 1 As含量 0.112** 0.270** -0.045 0.134** 0.142** 1 注: **表示在0.01级别(双尾)相关性显著。
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表 6 主成分分析特征值及方差贡献率
Table 6. Eigenvalues and variance contribution rates of principal component analysis
主成分 特征值 方差贡献率/% 累积方差贡献率/% 1 1.706 28.427 28.427 2 1.222 20.370 48.797 3 0.893 14.880 63.677 4 0.847 14.124 77.801 5 0.730 12.172 89.973 6 0.602 10.027 100.000
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表 7 成分旋转载荷矩阵
Table 7. Component rotation load matrix
指标 因子载荷量 第一主成分 第二主成分 pH值 0.520 0.536 Cu含量 0.781 0.076 Pb含量 0.012 0.680 Zn含量 0.652 -0.063 Cr含量 0.311 -0.643 As含量 0.549 -0.223
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