基于基体效应校正和对应分析的便携式X荧光光谱法对土壤重金属的研究

随着工业化和城市化的加深，城市土壤重金属污染状况愈发严重，而传统的实验室化学分析方法例如电感耦合等离子体质谱法分析周期较长，易产生废弃实验试剂二次污染环境。便携式X荧光光谱法是一种可以在野外现场直接进行快速、无损分析的测试手段，而基体效应是影响该方法测试准确度和精密度的最主要因素。当今较为常用的校正方法为传统线性回归法，该方法受离群值影响较大，处理后数据依然存在较大的偏差。本研究通过将常量元素的测试数据加入到待测元素的校正方程中，来减弱测试过程中基体效应的影响。利用便携式X荧光光谱仪对吉林大学各校区土壤样品的Cr，Ni，Cu，Zn和Pb重金属含量在原位条件下进行了快速测试，探究了对各重金属元素基体效应影响最大的常量元素，并结合偏最小二乘法及多元线性回归对原始谢尔曼方程进行调整，利用电感耦合等离子体质谱法作为参照，通过新方程对各重金属元素进行了基体效应校正，通过统计学参数对比该方法处理后的数据和经传统线性回归法处理后的数据的区别，并通过对应分析综合分析元素及样品间的相关性。结果表明常量元素是基体效应影响的重要元素，基于不同常量元素的基体效应校正方程效果较好，适用性Cr>Pb>Zn>Ni>Cu，校正后数据质量得到了明显提高，决定系数增大，回归图像更加集中，平均绝对误差、均方根误差等参数均进一步减小，校正效果优于传统的线性回归法。基体效应校正法主要是通过减小离群值的偏离程度来减小数据总体的平均误差和离散程度。处理后数据满足定量分析要求，可以推广至便携式X荧光光谱法对于土壤重金属快速的大面积扫面测试，检测环境质量。同时对应分析是一种多维数据维度与多维数据维度之间的分析方法，用于多种变量间的分类与相关性分析具有非常优秀的效果。

Study on Heavy Metal in Soil by Portable X-Ray Fluorescence Spectrometry Based on Matrix Effect Correction and Correspondence Analysis

With the deepening of industrialization and urbanization, urban soil heavy metal pollution is becoming more and more serious. At the same time, traditional laboratory chemical analysis methods such as inductively coupled plasma mass spectroscopy have long analysis cycles and are prone to secondary pollution of the environment by experimental waste reagents. Portable X-ray fluorescence spectrometry is a testing method that can be used for rapid and non-destructive analysis directly in the field, and matrix effect is the most important factor affecting the testing accuracy and precision. The more commonly used calibration method is the traditional linear regression method, which is influenced by outlying values and still has large deviations in the processed data. The study attenuated the matrix effects during testing by adding the data of the major elements to the correction equation of the elements to be tested. In this study, heavy metals of Cr, Ni, Cu, Zn and Pb in soil samples from each campus of Jilin University was rapidly tested by portable X-ray fluorescence spectrometry under in situ to investigate the major elements that had the greatest influence on the matrix effect of each heavy metal element. The original Sherman equation was adjusted by combining the partial least-square method and the multiple linear regression method, and the new equation was used to correct for the matrix effect of each heavy metal element under the data of inductively coupled plasma mass spectrometry a reference. The differences between the data processed by this method and the traditional linear regression method were compared by statistical parameters, and the correlation between elements and samples was also analyzed by correspondence analysis. The results show that the major elements are the important factor affected by the matrix effect, and the matrix effect correction equation based on different major elements is effective, with applicability Cr>Pb>Zn>Ni>Cu. The quality of the corrected data was significantly improved, the coefficient of determination increased, the regression images were concentrated, the mean absolute error and root mean square error was further reduced. The correction effect was better than the traditional linear regression method. The matrix effect correction method mainly reduces the overall average error and discrete degree of the data by reducing the deviation of outlying values. The processed data meet the quantitative analysis requirements and can be extended to portable X-ray fluorescence spectrometry for rapid large area testing of heavy metals to detect environmental quality. At the same time, correspondence analysis is an analysis method between multi-dimensional data dimensions and multi-dimensional data dimensions. It has excellent results for classification and correlation analysis between multiple variables.