光谱学与光谱分析, 2020, 40 (1): 119, 网络出版: 2020-04-04  

三维荧光光谱结合二阶校正方法同时测定水中两种酚类

Determination of Two Phenols in Water by Three Dimensional Fluorescence Spectroscopy Combined with Second-Order Calibration Method
作者单位
1 燕山大学河北省测试计量技术及仪器重点实验室, 河北 秦皇岛 066004
2 河北环境工程学院, 河北 秦皇岛 066102
摘要
水是生命之源, 人们日常生产生活离不开水。 近年来水体污染日趋严重, 已经危害到人类的健康。 酚类化合物(Phenolic Compound)是一种广泛存在且很难降解的有机污染物, 指的是芳香烃中苯环上的氢原子被羟基取代所生成的含羟基衍生物, 毒性很强, 对动植物及人类的生命活动有严重危害。 实验研究对象选取间苯二酚(resorcinol, RES)和对苯二酚(hydroquinone, HYD)来配制待测样本, 并且在其中3组预测样本中加入苯酚(phenol, PHE)作为干扰物, 待测样本和空白溶剂分别用FS920稳态荧光光谱仪(edinburgh instruments, EI)扫描得到荧光光谱数据。 对所得到的数据通过扣除空白溶剂法来消除拉曼散射的影响, 得到的数据在消除干扰的同时最大程度保留下来原光谱所包含的重要信息。 校正后光谱变得更加圆滑, 荧光强度显著增强, 因此, 校正处理后的光谱信息更为准确。 利用三维荧光光谱(EEM)结合平行因子分析(PARAFAC)和交替惩罚三线性分解(APTLD)两种二阶校正方法, 分别完成在不含干扰物和含有干扰物、 同时激发-发射光谱严重重叠时对间苯二酚、 对苯二酚的快速、 直接、 准确测量, 并给出定性、 定量分析结果。 PARAFAC算法对混合体系的组分数(即化学秩)较敏感, 组分数选取过大易使其陷入计算“沼泽”, 迭代次数增多, 计算耗时变长。 故本文利用核一致诊断法(CORCONDIA)预估计出准确的组分数, 保证PARAFAC算法更加快速准确。 从定性分析结果知, 当不含有干扰物时, PARAFAC能够准确分辨出间苯二酚和对苯二酚, 二者荧光峰位置极为接近, 很难用传统方法分辨, 体现出将三维荧光光谱技术与化学计量学二阶校正方法相结合所具有的“二阶优势”; 定量分析结果给出, 在有干扰物共存时, 分别应用两种二阶校正法解析光谱数据结果显示: PARAFAC的浓度预测回收率为93.4%±0.5%~97.1%±1.0%, 预测均方根误差小于0.190 mg·L-1; APTLD的浓度预测回收率为95.9%±1.6%~97.2%±0.8%, 预测均方根误差小于0.116 mg·L-1, 通过比较两种方法性能得: PARAFAC对待测物组分数敏感, 对待分解的光谱数据严格线性要求高; 而APTLD对混合物组分数不敏感, 计算速度快, 抗噪声能力较强, 结果稳定, 具有较明显的优势。
Abstract
Water is the source of life, which is indispensable to people’s diurnal production and life. In recent years, water contamination has become increasingly severe, which has endangered humanity health. Phenolic compounds are organic pollutants that are widespread and difficult to degrade, which refers to hydroxyl-containing derivatives produced by hydroxyl substitution of hydrogen atoms in benzene rings of aromatic hydrocarbons. They are highly toxic to animal, plant and human life activities. Resorcinol (RES) and hydroquinone (HYD) were selected as research object of experiment, and phenol (PHE) was added to three groups of predicted samplesas interference. The samples and blank solvent were scanned by the laboratory FS920 steady-state fluorescence spectrometer to obtain fluorescence spectrum data. The influence of Raman scattering would be eliminated through the deduction of blank solvents method. The obtained data contain the important information in the original spectrum with the greatest extent is preserved while eliminating interference. The spectrum becomes smoother and the fluorescence intensity raise significantly, so the spectral information is more accurate after correction. Second-order correction methods: parallel factor analysis (PARAFAC) and alternating penalty trilinear decomposition (APTLD) together with three-dimensional fluorescence spectroscopy (EEM) were used to measure RES and HYD in form of qualitative and quantitative analysis fast, directly and accurately in two cases: under interference and without interfering stuff meanwhile excitation-emission spectra overlap severely. Because PARAFAC algorithm is sensitive to the component number (i. e. chemical rank) of the mixture system, when the component number is too large the algotithem will arise: falling into the “swamp”, iterations number increases more time consuming. In this paper, Core Consistency Diagnosis (CORCONDIA) is used to estimate component number precisely, which ensures algorithm calculating faster and more accurate. As qualitative analysis results showed that PARAFAC can accurately distinguish RES and HYD without interference. The peak position of RES and HYD are very close, thus it is difficult to distinguish them via traditional methods and “second-order advantage” of combining three-dimensional fluorescence spectroscopy with second-order calibration is demonstrated. The results of quantitative analysis give out that the accuracy of this method is slightly reduced and RMSEP value increases slightly in the presence of interference, but these two methods can still complete the determination accurately. The recovery rate of PARAFAC is 93.4%±0.5%~97.1%±1.0% and the predicted root mean square error is less than 0.190 mg·L-1. Manwhile, the recovery rate of APTLD is 95.9%±1.6%~97.2%±0.8% and the predicted root mean square error is less than 0.116 mg·L-1. By comparing the performance of the above methods, we know PARAFAC is sensitive to the number of components in the samples and strictly linear to the decomposed spectral data. However APTLD has obvious advantages: being insensitive to the number of components, fast calculation speed, strong anti-noise ability, stable results, all of which highlight its advantages.

孙洋洋, 张立娟, 王玉田, 商凤凯, 王选瑞, 张慧. 三维荧光光谱结合二阶校正方法同时测定水中两种酚类[J]. 光谱学与光谱分析, 2020, 40(1): 119. SUN Yang-yang, ZHANG Li-juan, WANG Yu-tian, SHANG Feng-kai, WANG Xuan-rui, ZHANG Hui. Determination of Two Phenols in Water by Three Dimensional Fluorescence Spectroscopy Combined with Second-Order Calibration Method[J]. Spectroscopy and Spectral Analysis, 2020, 40(1): 119.

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