Measurement Technology and Instrument Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
Measurement Technology and Instrument Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China; Vocational and Technical College of Liuzhou, Liuzhou 545000, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2018 Dec 5;205:381-390. doi: 10.1016/j.saa.2018.07.045. Epub 2018 Jul 18.
Interference-free determination of polycyclic aromatic hydrocarbons (PAHs) in water pollution is proposed based on third-order correction algorithms with quadrilinear component modeling applied to the constructed four way fluorescence excitation-emission-sample data array with higher accuracy and better predictive ability than second-order (three-dimension) correction. Alternating weighted residue constraint quadrilinear decomposition (AWRCQLD), quadrilinear parallel factor analysis (4-PARAFAC), alternate penalty quadrilinear decomposition (APQLD) and alternate penalty trilinear decomposition (APTLD) are applied to acenaphthene (ANA), naphthalene (NAP) and fluorene (FLU) respectively. Fulvic acid affects PAHs determination seriously in real-world situation, so it is simulated as an interfering agent. Excitation-emission fluorescence matrixes (EEMs) of PAHs are measured at different volumes of fulvic acid simulated different interference conditions, to construct a four-way data array. After the four-way spectra data is analyzed by AWRCQLD, 4-PARAFAC, and APQLD, three-way EEMs analyzed by APTLD, results show that, on the one hand, PAHs can be measured more accurately with four-way data combined with third-order calibration than lower-order. On the other hand, AWRCQLD algorithm can reflect the superiority of third-order advantage better with higher recovery rate and smaller root mean square error, than other third-order or second-order correction algorithms.
提出了一种基于四线性分量建模的三阶校正算法,用于构建四路荧光激发-发射-样品数据阵列,以实现对水污染中多环芳烃(PAHs)的无干扰测定,该方法比二阶(三维)校正具有更高的准确性和更好的预测能力。交替加权残差约束四线性分解(AWRCQLD)、四线性平行因子分析(4-PARAFAC)、交替惩罚四线性分解(APQLD)和交替惩罚三线性分解(APTLD)分别应用于苊(ANA)、萘(NAP)和芴(FLU)。腐殖酸在实际情况下严重影响 PAHs 的测定,因此将其模拟为干扰剂。在不同体积的腐殖酸模拟不同干扰条件下,测量 PAHs 的激发-发射荧光矩阵(EEMs),以构建四路数据阵列。用 AWRCQLD、4-PARAFAC 和 APQLD 对四路光谱数据进行分析后,用 APTLD 对三向 EEMs 进行分析,结果表明,一方面,与低阶方法相比,结合三阶校正的四路数据可以更准确地测量 PAHs。另一方面,AWRCQLD 算法可以更好地反映三阶优势的优越性,具有更高的回收率和更小的均方根误差,优于其他三阶或二阶校正算法。