光谱学与光谱分析, 2019, 39 (3): 818, 网络出版: 2019-03-19   

基于二维相关荧光谱土壤中PAHs检测方法研究

Detection of PAHs in Soil Based on Two-Dimensional Correlation Fluorescence Spectroscopy
作者单位
1 天津农学院工程技术学院, 天津 300384
2 南开大学物理学院光子学中心, 天津 300071
3 天津农学院农业分析测试中心, 天津 300384
摘要
传统荧光光谱技术已被用于土壤中多环芳烃(PAHs)的检测, 但由于土壤体系的复杂性、 PAHs污染物的多样化和微量化, 传统的荧光光谱技术无法有效提取土壤中PAHs的特征信息。 为了解决上述问题, 提出并建立一种基于二维相关荧光谱土壤中多环芳烃的检测方法。 以土壤中典型的多环芳烃蒽和菲为研究对象, 配置38个蒽菲混合标准土壤样品(蒽和菲的浓度范围均为0.000 5~0.01 g·g-1), 在激发波长265~340 nm, 发射波长350~500 nm范围内采集了所有样品的三维荧光谱。 以激发波长为外扰, 对外扰变化的动态一维荧光谱进行相关计算, 得到每一样品的同步二维相关荧光谱。 研究了浓度均为0.005 g·g-1蒽菲混合土壤样品的三维荧光谱和同步二维相关荧光谱特性, 在同步谱主对角线398, 419, 444和484 nm处存在自相关峰, 其中, 398和484 nm荧光峰来自土壤中的菲, 419和444 nm荧光峰来自土壤中的蒽; 在主对角线外侧, 蒽和菲两组荧光峰之间存在负的交叉峰, 进一步验证了其来源不同; 同时, 在(408, 434) nm和(434, 467) nm处出现交叉峰, 其中408和434 nm荧光峰来自土壤中的菲, 467 nm荧光峰来自土壤中的蒽。 指出与三维荧光谱表征的信息相比, 二维相关荧光谱不仅能提取更多的特征信息(408和467 nm的特征峰在三维荧光谱中未被表征), 而且还能提供荧光峰之间的相互关系, 对其来源进行有效解析。 在上述研究二维相关荧光谱特性的基础上, 基于同步相关谱矩阵(38×151×151)建立了定量分析土壤中蒽和菲污染物浓度的多维偏最小二乘(N-PLS)模型, 对蒽的校正和预测相关系数分别为0.986和0.985, 校正均方根误差(RMSEC)和预测均方根误差(RMSEP)分别为4.33×10-4和5.55×10-4 g·g-1; 对菲的校正和预测相关系数分别为0.981和0.984, RMSEC和RMSEP分别为5.20×10-4和4.80×10-4 g·g-1。 为了比较, 基于三维荧光光谱矩阵(38×16×151)建立了定量了分析土壤中蒽和菲的N-PLS模型, 对蒽的校正和预测相关系数分别为0.981和0.972, RMSEC和RMSEP分别为5.09×10-4和6.74×10-4 g·g-1; 对菲的校正和预测相关系数分别为0.957和0.956, RMSEC和RMSEP分别为7.36×10-4和7.77×10-4 g·g-1。 指出, 对于土壤中的蒽和菲检测, 基于二维相关荧光谱的N-PLS模型的相关系数r, RMSEC和RMSEP都要优于基于三维荧光谱的N-PLS模型。 研究结果表明: 所提出和建立的方法—二维相关荧光谱直接检测土壤中PAHs污染物不仅可行, 而且能提供更好的分析结果。 该研究为激光诱导荧光结合相关谱技术现场直接检测土壤中多环芳烃污染物提供了理论和实验基础, 具有较好的应用前景。
Abstract
The traditional fluorescence spectroscopy has been used for the detection of polycyclic aromatic hydrocarbons (PAHs) in soil. However, due to the complexity of soil system and the diversification and trace of PAHs pollutants, the traditional fluorescence spectroscopy cannot effectively extract the characteristic information of PAHs in soil. In order to solve the above problem, a new detection method of PAHs in soil was proposed and established based on two-dimensional (2D) correlation fluorescence spectroscopy. The typical PAHs pollutants of anthracene and phenanthrene in soil were used as research targets, and 38 mixture samples (the concentration of anthracene and phenanthrene in soil were between 0.000 5 and 0.01 g·g-1) were prepared. Three-dimensional (3D) fluorescence spectra of all samples were collected in the excitation wavelength range of 265~340 nm within an interval of 5 nm and in the emission wavelength range of 350~500 nm within an interval of 1 nm. And synchronous 2D correlation fluorescence spectra of all samples were calculated based on one-dimensional (1D) fluorescence spectra under the excitation perturbation. The characteristics of 3D fluorescence spectrum and synchronous 2D correlation fluorescence spectrum of the mixture of anthracene and phenanthrene were studied in soil (anthracene: 0.005 g·g-1, phenanthrene: 0.005 g·g-1). In the synchronous 2D correlation fluorescence spectrum, four auto-peaks were observed at 398, 419, 444 and 484 nm along the main diagonal. Among them, the fluorescence peaks of 398 and 484 nm came from the phenanthrene in the soil, and the fluorescence peaks of 419 and 444 nm came from the anthracene in the soil. At the outside of the main diagonal line, there were negative cross peaks between anthracene and phenanthrene fluorescence peaks, which further verified that the sources were different. At the same time, there were two cross peaks at (408, 434) nm and (434, 467) nm, and the peaks at 408 and 434 nm were assigned to phenanthrene and 467 nm was assigned to anthracene in soil. It was pointed out that, compared with traditional 3D fluorescence spectroscopy, 2D correlation fluorescence spectroscopy could not only extract more characteristic information (the characteristic peaks of 408 and 467 nm are not represented in the 3D fluorescence spectrum), but also provide the relationship between fluorescence peaks, and effectively analyse their sources. On the basis of the characteristics of the 2D correlation fluorescence spectra, the N-way partial least squares (N-PLS) models for detecting the contaminants of anthracene and phenanthrene in soil were developed based on synchronous 2D correlation fluorescence spectral matrices (38×151×151). For anthracene in soil, the correlation coefficients r were 0.986 and 0.985 in calibration and prediction set; the mean square root error of calibration (RMSEC) and the root mean square error of the prediction (RMSEP) were 4.33×10-4 and 5.55×10-4 g·g-1, respectively. For phenanthrene in soil, the correlation coefficients r were 0.981 and 0.984 in calibration and prediction set; the RMSEC and the RMSEP were 5.20×10-4 and 4.80×10-4 g·g-1, respectively. In order to compare, the N-PLS models for quantitative analysis of anthracene and phenanthrene in soil were established based on a 3D fluorescence spectral matrices(38×16×151). For anthracene in soil, the correlation coefficients r were 0.981 and 0.972 in calibration and prediction set; the RMSEC and the RMSEP were 5.09×10-4 and 6.74×10-4 g·g-1, respectively. For phenanthrene in soil, the correlation coefficients r were 0.957 and 0.956 in calibration and prediction set; the RMSEC and the RMSEP were 7.36×10-4 and 7.77×10-4 g·g-1, respectively. It was pointed out that, for the detection of anthracene and phenanthrene in soil, the correlation coefficients r, RMSEC and RMSEP of N-PLS models were better based on 2D correlation fluorescence spectra than 3D fluorescence spectra. The results showed that the direct detection of PAHs contaminants in soil based on 2D correlation fluorescence spectroscopy is not only feasible, but also can provide better analysis results. This study provides a theoretical and experimental basis for direct detection of PAHs in soil by laser induced fluorescence combined with 2D correlation technology, having a good application prospect.

杨仁杰, 王斌, 董桂梅, 杨延荣, 吴楠, 孙国红, 张伟玉, 刘海学. 基于二维相关荧光谱土壤中PAHs检测方法研究[J]. 光谱学与光谱分析, 2019, 39(3): 818. YANG Ren-jie, WANG Bin, DONG Gui-mei, YANG Yan-rong, WU Nan, SUN Guo-hong, ZHANG Wei-yu, LIU Hai-xue. Detection of PAHs in Soil Based on Two-Dimensional Correlation Fluorescence Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2019, 39(3): 818.

本文已被 3 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!