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为了满足土壤重金属快速准确检测的需求,同时为土壤的重金属污染防治和农业的可持续发展提供理论指导,该研究利用激光诱导击穿光谱(laser-induced breakdown spectroscopy,LIBS)技术结合定标曲线法和化学计量学方法对土壤中重金属铅(Pb)和镉(Cd)元素进行定量分析。在获取LIBS数据之后,结合土壤LIBS发射谱线中Pb和Cd谱峰信息以及美国国家标准与技术研究院(national institute of standards and technology,NIST)的标准原子光谱数据库,选取了Pb和Cd的特征谱线分别为Pb I 405.78和Cd I 361.05 nm。首先对谱线信息进行预处理后,根据谱峰信息和元素的含量,分别建立了基于谱线峰强度、归一化后洛伦兹拟合强度、谱峰积分强度与对应元素浓度之间的关系模型和定标曲线。对于Pb元素的3种定标方法得到的线性关系的决定系数(R2)分别为0.983 85、0.970 97、0.993 21,且模型反演的结果与实际值的相对误差较小;而Cd元素的3种定标方法没有得到明显线性关系。然后运用偏最小二乘回归(partial least-squares regression,PLSR)建立了土壤Pb和Cd元素的定量分析模型,Pb元素PLSR模型的结果与定标曲线法的结果类似,其预测的相关系数(RP)为0.948 5,预测均方根误差(RMSEP)为2.044 mg/g;而Cd元素的PLSR模型的结果比起定标曲线法有较大提升,其预测的相关系数(RP)为0.994 9,预测均方根误差(RMSEP)为97.05μg/g,结果说明PLSR方法在光谱化学分析领域中比定标曲线法进行定量分析有更好的适用性。研究表明,LIBS技术能够实现对土壤重金属Pb和Cd含量的定量检测,为开发实时便携式LIBS土壤重金属检测仪提供了理论基础。
In order to meet the need of rapid and accurate determination of heavy metals in soil, and to provide theoretical guidance for the prevention and control of heavy metal pollution in soil and the sustainable development of agriculture, laser-induced breakdown spectroscopy (LIBS) and calibration curve method And stoichiometry to quantitatively analyze heavy metal lead (Pb) and cadmium (Cd) in soils. After obtaining LIBS data, the characteristics of Pb and Cd were selected based on the Pb and Cd peak information of soil LIBS emission spectra and the standard atomic spectroscopy database of the National Institute of Standards and Technology (NIST) Spectra were Pb I 405.78 and Cd I 361.05 nm, respectively. Firstly, the spectral information is pre-processed, and based on the spectral peak information and the content of the elements, spectral intensities of the spectral peaks, the normalized Lorentzian fitting intensities, the integrated spectral peak intensities and the corresponding element concentrations Relationship model and calibration curve. The determination coefficients (R2) of the linear relationship obtained by the three calibration methods for Pb element are respectively 0.983 85, 0.970 97 and 0.993 21, and the relative error between the model inversion result and the actual value is small. However, The calibration method did not get a significant linear relationship. The quantitative analysis model of Pb and Cd in soils was established by partial least-squares regression (PLSR). The results of Pb element PLSR model were similar to those of calibration curve method. The predicted correlation coefficient (RP) ) Was 0.948 5, and the root mean square error of prediction (RMSEP) was 2.044 mg / g. The results of PLSR model of Cd element increased greatly compared with the calibration curve method, and the predicted correlation coefficient (RP) was 0.994 9, The root mean square error of prediction (RMSEP) was 97.05 μg / g, indicating that the PLSR method has better applicability in the field of spectrochemical analysis than the calibration curve method. The research shows that LIBS technology can quantitatively detect the content of heavy metals Pb and Cd in soil and provides the theoretical basis for the development of real-time portable LIBS soil heavy metal detector.