中国地质学会岩矿测试技术专业委员会、国家地质实验测试中心主办

应用近红外光谱法研究泻湖湿地沉积物重金属活动态特征及生态风险评价

尚文郁, 谢曼曼, 王淑贤, 孙青, 岑况. 应用近红外光谱法研究泻湖湿地沉积物重金属活动态特征及生态风险评价[J]. 岩矿测试, 2020, 39(4): 597-608. doi: 10.15898/j.cnki.11-2131/td.202001010001
引用本文: 尚文郁, 谢曼曼, 王淑贤, 孙青, 岑况. 应用近红外光谱法研究泻湖湿地沉积物重金属活动态特征及生态风险评价[J]. 岩矿测试, 2020, 39(4): 597-608. doi: 10.15898/j.cnki.11-2131/td.202001010001
Wen-yu SHANG, Man-man XIE, Shu-xian WANG, Qing SUN, Kuang CEN. Detection of Heavy Metals Mobile Fraction in Lagoonal Wetland Sediment Using Near-Infrared Spectroscopy and Ecological Risk Assessment[J]. Rock and Mineral Analysis, 2020, 39(4): 597-608. doi: 10.15898/j.cnki.11-2131/td.202001010001
Citation: Wen-yu SHANG, Man-man XIE, Shu-xian WANG, Qing SUN, Kuang CEN. Detection of Heavy Metals Mobile Fraction in Lagoonal Wetland Sediment Using Near-Infrared Spectroscopy and Ecological Risk Assessment[J]. Rock and Mineral Analysis, 2020, 39(4): 597-608. doi: 10.15898/j.cnki.11-2131/td.202001010001

应用近红外光谱法研究泻湖湿地沉积物重金属活动态特征及生态风险评价

  • 基金项目:
    国家自然科学基金青年科学基金项目“基于红外光谱的金川泥炭中有机碳、腐植酸、木质素等古气候替代指标快速分析方法及在古气候研究中的应用”(41402325)
详细信息
    作者简介: 尚文郁, 硕士, 助理研究员, 从事环境地球化学及气候替代指标研究。E-mail:shangwenyu@cags.ac.cn
    通讯作者: 岑况, 博士, 教授, 从事矿床地球化学及环境地球化学研究。E-mail:cenkuang@cugb.edu.cn
  • 中图分类号: O657.33

Detection of Heavy Metals Mobile Fraction in Lagoonal Wetland Sediment Using Near-Infrared Spectroscopy and Ecological Risk Assessment

More Information
  • 沉积物中的重金属元素经自然作用下可以活动态进行迁移,具有潜在生物可利用性及潜在的区域生态风险。利用近红外光谱(NIRS)技术开展不同基体类型样品响应机理研究,可为评估重金属活动态提供无损、快速的分析方法,为生态风险研究提供依据。天津七里海泻湖湿地沉积物具有低有机质-高黏土含量的特征,本文基于近红外光谱分析技术,建立了沉积物中Co、Ni、Cu、Zn、Cd、Pb重金属活动态组分含量近红外光谱-偏最小二乘回归预测模型。实验结果表明:样品在7290~6390cm-1和4683~4000cm-1波段存在的双羟基O-H伸缩振动、AlAl-OH及Al(Mg)-OH弯曲振动特征吸收,间接指示了重金属元素活动态含量。光谱预测结果显示,近百年来七里海沉积物中Co、Ni、Cu、Zn、Cd、Pb活动态组分的变化特征对应了当地1934-1948年、1956-1963年、1976年至今三次较明显的升温过程,也对应了1980年七里海水库建设等大型人为扰动。本研究样品中Co、Ni、Cu、Zn、Cd、Pb总量及活动态均低于国家标准中规定的生态风险阈值,七里海内村镇及周边农田来自湿地释放的重金属生态风险极低。
  • 加载中
  • 图 1  研究区及钻孔位置

    Figure 1. 

    图 2  均一化预处理对Co校正模型的优化:(a)未采取均一化;(b)经过MSC处理

    Figure 2. 

    图 3  基线校正对Zn校正模型的优化:(a)采取基线校正; (b)一阶导转换; (c)二阶导转换

    Figure 3. 

    图 4  光谱预测结果与化学测定结果的相关性

    Figure 4. 

    图 5  校正模型第一、第二因子负载值与样品光谱对应情况

    Figure 5. 

    图 6  活动态重金属与NIRS分段峰面积1~4(Peak Area, PA)的聚类分析

    Figure 6. 

    图 7  重金属活动态光谱预测值与测定值随深度变化特征(黑线表示测定值,红线表示预测值)

    Figure 7. 

    表 1  校正模型各组分拟合结果

    Table 1.  Fitting results of each component in correction model

    组分 样品数量 最低值(μg/g) 最高值(μg/g) 平均值(μg/g) 相关系数Rc2 校正误差(μg/g)
    总量Co 86 11.98 17.48 15.36 0.72 1.21
    活动态Co 86 4.01 7.55 5.52 0.98 0.01
    总量Ni 86 31.17 52.93 41.48 0.69 3.46
    活动态Ni 86 8.31 15.80 11.96 0.98 0.27
    总量Cu 86 26.13 59.48 40.32 0.71 4.02
    活动态Cu 86 14.76 29.49 22.20 0.98 0.52
    总量Zn 86 109.66 185.70 151.12 0.64 14.86
    活动态Zn 86 27.23 63.89 42.11 0.98 0.59
    总量Cd 86 0.26 0.58 0.40 0.80 0.11
    活动态Cd 86 0.08 0.27 0.17 0.98 0.01
    总量Pb 86 21.41 31.63 26.10 0.72 1.80
    活动态Pb 86 11.30 21.91 16.75 0.99 0.16
    下载: 导出CSV

    表 2  七里海样品中重金属活动态含量与国家标准中最低筛选值对比

    Table 2.  Comparison of heavy metals mobile fraction concentration in Qilihai samples and their minimum filter values in national standard

    重金属 最低值(μg/g) 最高值(μg/g) 平均值(μg/g) 标准中规定的最低筛选值(μg/g)
    总量Co 11.98 17.48 15.36 20
    活动态Co 4.01 7.55 5.52
    总量Ni 31.17 52.93 41.48 150
    活动态Ni 8.31 15.80 11.96
    总量Cu 26.13 59.48 40.32 100
    活动态Cu 14.76 29.49 22.20
    总量Zn 109.66 185.70 151.12 300
    活动态Zn 27.23 63.89 42.11
    总量Cd 0.26 0.58 0.40 0.8
    活动态Cd 0.08 0.27 0.17
    总量Pb 21.41 31.63 26.10 170
    活动态Pb 11.30 21.91 16.75
    下载: 导出CSV
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出版历程
收稿日期:  2020-01-01
修回日期:  2020-06-04
录用日期:  2020-06-15

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