Zhiwei Wang, Peiliang Wu, Yuhan Zhao, Xinyi Li, Deming Kong
{"title":"将激发-发射矩阵荧光光谱和化学计量学应用于乳化油浓度的定量分析。","authors":"Zhiwei Wang, Peiliang Wu, Yuhan Zhao, Xinyi Li, Deming Kong","doi":"10.1016/j.saa.2024.125423","DOIUrl":null,"url":null,"abstract":"<p><p>Emulsified oil concentration is an important index for quantitative analysis of sea surface oil spill pollution, and the development of a fast and effective quantitative analysis method for emulsified oil concentration plays a crucial role in the estimation of oil spill volume and post-spill assessment. A quantitative analysis method for emulsified oil concentration based on excitation-emission matrix (EEM) fluorescence spectroscopy and chemometrics was proposed. Firstly, the EEM fluorescence spectra of two emulsified oils were measured using a FLS1000 fluorescence spectrometer. Then, the measured EEM fluorescence spectra were decomposed by parallel factor analysis (PARAFAC), and several key excitation wavelengths were filtered from the loading matrix obtained from the decomposition. Subsequently, the three-band fluorescence index (TBFI) at these excitation wavelengths was calculated and combined with the optimal band selection algorithm, from which the optimal emission band combinations were selected. Finally, the selected optimal emission bands were combined with partial least squares regression (PLSR) to establish a prediction model for emulsified oil concentration. By comparing the prediction results with those based on PARAFAC-PLSR and multivariate curve resolved-alternating least squares (MCR-ALS)-PLSR models, the TBFI-PLSR model showed the best results in the quantitative analysis of emulsified oil concentration. The coefficient of determination, mean square relative error, and ratio of performance to interquartile distance for the gasoline and diesel fuel emulsion validation sets were 0.93, 3.67%, 4.72, and 0.93, 3.72%, 4.60, respectively.</p>","PeriodicalId":94213,"journal":{"name":"Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy","volume":"328 ","pages":"125423"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of excitation-emission matrix fluorescence spectroscopy and chemometrics for quantitative analysis of emulsified oil concentration.\",\"authors\":\"Zhiwei Wang, Peiliang Wu, Yuhan Zhao, Xinyi Li, Deming Kong\",\"doi\":\"10.1016/j.saa.2024.125423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Emulsified oil concentration is an important index for quantitative analysis of sea surface oil spill pollution, and the development of a fast and effective quantitative analysis method for emulsified oil concentration plays a crucial role in the estimation of oil spill volume and post-spill assessment. A quantitative analysis method for emulsified oil concentration based on excitation-emission matrix (EEM) fluorescence spectroscopy and chemometrics was proposed. Firstly, the EEM fluorescence spectra of two emulsified oils were measured using a FLS1000 fluorescence spectrometer. Then, the measured EEM fluorescence spectra were decomposed by parallel factor analysis (PARAFAC), and several key excitation wavelengths were filtered from the loading matrix obtained from the decomposition. Subsequently, the three-band fluorescence index (TBFI) at these excitation wavelengths was calculated and combined with the optimal band selection algorithm, from which the optimal emission band combinations were selected. Finally, the selected optimal emission bands were combined with partial least squares regression (PLSR) to establish a prediction model for emulsified oil concentration. By comparing the prediction results with those based on PARAFAC-PLSR and multivariate curve resolved-alternating least squares (MCR-ALS)-PLSR models, the TBFI-PLSR model showed the best results in the quantitative analysis of emulsified oil concentration. The coefficient of determination, mean square relative error, and ratio of performance to interquartile distance for the gasoline and diesel fuel emulsion validation sets were 0.93, 3.67%, 4.72, and 0.93, 3.72%, 4.60, respectively.</p>\",\"PeriodicalId\":94213,\"journal\":{\"name\":\"Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy\",\"volume\":\"328 \",\"pages\":\"125423\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spectrochimica acta. 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Application of excitation-emission matrix fluorescence spectroscopy and chemometrics for quantitative analysis of emulsified oil concentration.
Emulsified oil concentration is an important index for quantitative analysis of sea surface oil spill pollution, and the development of a fast and effective quantitative analysis method for emulsified oil concentration plays a crucial role in the estimation of oil spill volume and post-spill assessment. A quantitative analysis method for emulsified oil concentration based on excitation-emission matrix (EEM) fluorescence spectroscopy and chemometrics was proposed. Firstly, the EEM fluorescence spectra of two emulsified oils were measured using a FLS1000 fluorescence spectrometer. Then, the measured EEM fluorescence spectra were decomposed by parallel factor analysis (PARAFAC), and several key excitation wavelengths were filtered from the loading matrix obtained from the decomposition. Subsequently, the three-band fluorescence index (TBFI) at these excitation wavelengths was calculated and combined with the optimal band selection algorithm, from which the optimal emission band combinations were selected. Finally, the selected optimal emission bands were combined with partial least squares regression (PLSR) to establish a prediction model for emulsified oil concentration. By comparing the prediction results with those based on PARAFAC-PLSR and multivariate curve resolved-alternating least squares (MCR-ALS)-PLSR models, the TBFI-PLSR model showed the best results in the quantitative analysis of emulsified oil concentration. The coefficient of determination, mean square relative error, and ratio of performance to interquartile distance for the gasoline and diesel fuel emulsion validation sets were 0.93, 3.67%, 4.72, and 0.93, 3.72%, 4.60, respectively.