重庆岩溶地质高背景区土壤−农作物系统重金属累积特征及影响因素

余飞, 罗恺, 王佳彬, 李瑜, 周皎, 王锐, 余亚伟, 张云逸. 重庆岩溶地质高背景区土壤−农作物系统重金属累积特征及影响因素[J]. 中国岩溶, 2023, 42(1): 71-83. doi: 10.11932/karst20230106
引用本文: 余飞, 罗恺, 王佳彬, 李瑜, 周皎, 王锐, 余亚伟, 张云逸. 重庆岩溶地质高背景区土壤−农作物系统重金属累积特征及影响因素[J]. 中国岩溶, 2023, 42(1): 71-83. doi: 10.11932/karst20230106
YU Fei, LUO Kai, WANG Jiabin, LI Yu, ZHOU Jiao, WANG Rui, YU Yawei, ZHANG Yunyi. Characteristics and influencing factors of heavy metal accumulation in soil-crop system in the karst area with high geological background of Chongqing[J]. Carsologica Sinica, 2023, 42(1): 71-83. doi: 10.11932/karst20230106
Citation: YU Fei, LUO Kai, WANG Jiabin, LI Yu, ZHOU Jiao, WANG Rui, YU Yawei, ZHANG Yunyi. Characteristics and influencing factors of heavy metal accumulation in soil-crop system in the karst area with high geological background of Chongqing[J]. Carsologica Sinica, 2023, 42(1): 71-83. doi: 10.11932/karst20230106

重庆岩溶地质高背景区土壤−农作物系统重金属累积特征及影响因素

  • 基金项目: 重庆市科学基金委(cstc2018jszx-zdyfxmX0006);重庆市规划和自然资源局((2019)128-12)
详细信息
    作者简介: 余飞(1989-),男,硕士,工程师,主要研究方向为土壤地球化学、环境地球化学。E-mail:yfcags@126.com
    通讯作者: 李瑜(1986 -),男,硕士,高级工程师,主要从事土地质量地球化学调查。E-mail:395904623@qq.com
  • 中图分类号: P595;X142

Characteristics and influencing factors of heavy metal accumulation in soil-crop system in the karst area with high geological background of Chongqing

More Information
  • 为了揭示重庆岩溶地质高背景区土壤-农作物系统中重金属的迁移累积特征,选择在重庆市南部典型岩溶区,系统地采集大宗农作物(水稻、玉米和红薯)及其耕层土壤84组,分析测定农作物及耕层土壤中重金属砷(As)、镉(Cd)、铬(Cr)、铜(Cu)、汞(Hg)、镍(Ni)、锌(Zn)含量及理化性质,采用地统计、生物富集因子及皮尔逊相关系数分析等方法,开展重金属元素在重庆岩溶地质高背景地区土壤−农作物系统中累积特征及影响因素。结果表明,研究区水稻田、玉米地和红薯地耕层土壤重金属平均含量均高于重庆市和全国表层土壤背景值,呈现不同程度的积累,其中Cd元素富集现象较为突出。依据GB 15618-2018和GB 2762-2017,耕层土壤种Cd超标率达41.59%,水稻、玉米和红薯中Cd超标率分别为5.89%、6.25%和5.56%,显示出岩溶地质高背景区虽然土壤中重金属含量总量高,但生物有效性较低。相关分析显示,土壤-农作物系统Cd等重金属含量主要受土壤pH、土壤质地和土壤中铁锰氧化物影响。

  • 加载中
  • 图 1  研究区采样点位分布示意图

    Figure 1. 

    图 2  研究区农作物重金属分布箱式图

    Figure 2. 

    图 3  研究区不同农作物重金属富集系数

    Figure 3. 

    图 4  研究区土壤pH与Cd富集系数相关关系

    Figure 4. 

    图 5  研究区土壤pH与Cd富集系数散点图

    Figure 5. 

    图 6  研究区土壤CaO与Cd富集系数、土壤pH相关关系

    Figure 6. 

    表 1  土壤元素分析方法与检出限

    Table 1.  Element analysis method and detection limit of soil

    指标测定方法检出限/mg·kg−1 指标测定方法检出限/mg·kg−1
    Al2O3X射线荧光光谱法0.05Se原子荧光光谱法0.01
    CaOX射线荧光光谱法0.05As原子荧光光谱法0.2
    K2OX射线荧光光谱法0.05Hg原子荧光光谱法0.000 5
    MgOX射线荧光光谱法0.05Mn等离子体光量计法10
    Na2OX射线荧光光谱法0.1Cu等离子体发射光谱法1
    TFe2O3X射线荧光光谱法0.05Ni等离子体发射光谱法1
    SiO2X射线荧光光谱法0.1Cd等离子体质谱法0.02
    CrX射线荧光光谱法3pHpH计电极法0.1
    ZnX射线荧光光谱法1
    下载: 导出CSV

    表 2  农作物元素分析方法与检出限

    Table 2.  Element analysis method and detection limit of crop

    指标测定方法检出限/mg·kg−1指标测定方法检出限/mg·kg−1
    As等离子体质谱法0.03Hg等离子体质谱法0.000 5
    Cd等离子体质谱法0.000 1Ni等离子体质谱法0.2
    Cr等离子体质谱法0.2Zn等离子体光谱法0.05
    Cu等离子体质谱法1
    下载: 导出CSV

    表 3  研究区不同农作物耕层土壤重金属含量特征(mg·kg−1

    Table 3.  Concentrations of heavy metals in the top soil of different crops in the study area (mg·kg−1

    耕层土类型统计值AsCdCrCuHgNiZnpH
    水稻耕层土最小值 3.33 0.10 52.7 15.8 0.03 17.1 46.54.51
    最大值22.532.45131.888.10.2554.4149.18.72
    平均值9.720.5479.634.70.1133.696.17.03
    变异系数0.510.780.230.350.480.270.240.16
    玉米耕层土最小值3.470.0761.920.10.0413.751.94.90
    最大值26.523.78272.0120.20.68119.5180.59.20
    平均值11.350.5288.838.40.1238.5101.67.18
    变异系数0.430.140.330.320.170.320.560.78
    红薯耕层土最小值3.130.1141.714.70.0413.045.54.88
    最大值20.531.14119.986.50.3362.7179.28.20
    平均值11.110.4880.935.00.1235.898.47.16
    变异系数0.410.520.270.450.560.340.300.15
    研究区耕层土壤平均值11.530.5184.8337.620.1136.6299.997.06
    重庆表层土壤背景值[14]6.620.2874.424.60.06931.681.9
    中国表层土壤背景值[15]9.10.1563230.052667
    广西岩溶地区平均值[17]26.31.004147310.18538130
    重庆黑色岩系区平均值[18]9.1634433.293.9193
    下载: 导出CSV

    表 4  研究区不同农作物重金属含量特征(mg·kg−1

    Table 4.  Concentrations of heavy metals in different crops in the study area(mg·kg−1

    农作物元素极小值极大值均值标准差富集系数GB 2762-2017超标率/%
    水稻As0.050.260.130.050.0150.50
    Cd0.010.270.050.060.1570.25.88
    Cr0.100.140.120.010.00210
    Cu0.604.572.300.910.071
    Hg0.0020.0080.0050.0020.0510.020
    Ni0.091.400.240.240.008
    Zn16.031.921.13.640.234
    玉米As0.030.070.040.010.0040.50
    Cd0.0020.300.040.060.1250.16.25
    Cr0.090.140.110.010.00110
    Cu1.4710.092.671.550.080
    Hg0.0010.0050.0020.0010.0230.020
    Ni0.121.050.250.180.007
    Zn15.043.525.46.130.270— 
    红薯As0.040.130.090.020.0100.50
    Cd0.010.100.040.020.1020.15.56
    Cr0.230.410.270.040.0040.50
    Cu4.5111.997.932.000.255
    Hg0.0010.0040.0020.0010.0260.010
    Ni0.291.710.590.400.019
    Zn7.6514.610.82.080.120
    下载: 导出CSV

    表 5  研究区土壤重金属与pH、氧化物含量的Pearson相关系数表(n=113)

    Table 5.  Pearson correlation of soil heavy metals with pH and oxide contents in the study area (n=113)

    元素pHNa20MgOAl2O3SiO2K2OCaOMnTFe2O3Se
    As0.135−.285**−0.0870.175−0.127−0.209*−0.0700.290**0.382**0.191*
    Cd0.162−0.0660.0860.190*−0.305**−0.1170.1170.0060.296**0.396**
    Cr0.219*−0.0920.1400.478**−0.427**−0.148−0.0160.1230.671**0.320**
    Cu0.056−0.0550.0240.224*−0.391**−0.1580.0300.0650.743**0.509**
    Hg0.142−0.189*−0.0390.159−0.243**−0.297**0.1210.0520.245**0.311**
    Ni0.1280.0550.0120.602**−0.503**0.078−0.0210.240*0.775**0.289**
    Zn0.1580.116−0.0610.499**−0.494**0.258**−0.0210.303**0.756**0.426**
    **: P<0.01, 在0.01水平上显著相关; *: P<0.05, 在0.05水平上显著相关。
    下载: 导出CSV

    表 6  研究区Cd富集系数与pH、氧化物含量的Pearson相关系数表

    Table 6.  Pearson correlation of Cd enrichment coefficient with pH and oxide contents in the study area

    农作物pHNa2OMgOAl2O3SiO2K2OCaOMnTFe2O3Se
    水稻−0.2910.026−0.1290.0620.2640.189−0.236−0.258−0.097−0.307
    玉米−0.111−0.1380.001−0.1390.284−0.039−0.192−0.174−0.153−0.201
    红薯−0.653**0.008−0.280−0.3980.659**−0.320−0.306−0.553*−0.209−0.455
    **: P<0.01, 在0.01水平上显著相关; *: P<0.05, 在0.05水平上显著相关。
    下载: 导出CSV
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出版历程
收稿日期:  2020-11-28
刊出日期:  2023-02-25

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