Abstract
Parallel factor (PARAFAC) analysis enables a quantitative analysis of excitation-emission matrix (EEM). The impact of a spectral variability stemmed from a diverse dataset on the representativeness of the PARAFAC model needs to be examined. In this study, samples from a river, effluent of a wastewater treatment plant, and algae secretion were collected and subjected to PARAFAC analysis. PARAFAC models of global dataset and individual datasets were compared. It was found that the peak shift derived from source diversity undermined the accuracy of the global model. The results imply that building a universal PARAFAC model that can be widely available for fitting new EEMs would be quite difficult, but fitting EEMs to existing PARAFAC model that belong to a similar environment would be more realistic. The accuracy of online monitoring strategy that monitors the fluorescence intensities at the peaks of PARAFAC components was examined by correlating the EEM data with the maximum fluorescence (Fmax) modeled by PARAFAC. For the individual datasets, remarkable correlations were obtained around the peak positions. However, an analysis of cocktail datasets implies that the involvement of foreign components that are spectrally similar to local components would undermine the online monitoring strategy.
Highlights
Fitted to new excitation-emission matrix (EEM) obtained from different sources[13,16,17,18,19]
Samples from a river (76 samples), effluent of a wastewater treatment plant (62 samples), and algae excretion (85 samples) were collected and subjected to following analysis. They are named as natural organic matter (NOM), effluent organic matter (EfOM), and extracellular organic matter (EOM) hereinafter
A global dataset that contains all samples was subjected to Parallel Factor (PARAFAC) analysis and the obtained global model was compared with each individual model
Summary
Fitted to new EEMs obtained from different sources[13,16,17,18,19]. online monitoring of DOM using EEM-PARAFAC has drawn a lot of attention, and many studies have referred to the possibility of online monitoring with this new technique[13,16,20,21]. In terms of online monitoring, a commonly proposed strategy is to monitor key pairs of excitation-emission wavelength at the componential peaks that were determined by PARAFAC modeling[13,16,21]. This method assumed that the fluorescence overlap is much gentler at the target wavelengths, so that the maximum fluorescence (Fmax) of each component in a sample (which is known to be proportional to the concentration of the corresponding component14,22,23) could be estimated quite accurately from the measurement at the excitation/emission wavelengths of the peaks. Whether monitoring fluorescence intensity at the peaks of PARAFAC components was feasible to estimate the Fmax (especially during a contamination event) was evaluated
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