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A chemometric analysis on the fluorescent dissolved organic matter in a full-scale sequencing batch reactor for municipal wastewater treatment 被引量:3
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作者 Chen Qian Wei Chen +1 位作者 Wei-Hua Li Han-Qing Yu 《Frontiers of Environmental Science & Engineering》 SCIE EI CAS CSCD 2017年第4期179-186,共8页
Rapid monitoring of water quality is crucial to the operation of municipal wastewater treatment plants (WWTPs). Fluorescence excitation-emission matrix (EEM) in combination with parallel lhctor analysis (PARAFAC... Rapid monitoring of water quality is crucial to the operation of municipal wastewater treatment plants (WWTPs). Fluorescence excitation-emission matrix (EEM) in combination with parallel lhctor analysis (PARAFAC) has been used as a powerful tool for the characterization of dissolved organic matter (DOM) in WWTPs. However, a recent work has revealed the drawback of PARAFAC analysis, i.e., overestimating the component number. A novel method, parallel lhctor framework-clustering analysis (PFFCA),"has been cleveloped in our earlier work to resolve this drawback of PARAFAC. In the present work, both PARAFAC and PFFCA were used to analyze the EEMs of water samples from a full-scale WWTP from a practical application point of view. The component number and goodness-of- fit from these two methods were compared and the relationship between the relative score change of component and the actual concentration was investigated to evaluate the estimation error introduced by 9 both methods. PFFCA score and actual concentration exhibited a higher correlation coefficient (R- = 0.870) compared with PARAFAC (R2〈 0.771), indicating that PFFCA provided a more accurate relative change estimation than PARAFAC. The results suggest that use of PARAFAC may cause confusion in selecting the component number, while EEM-PFFCA is a more reliable alternative approach for monitoring water quality in WWTPs. 展开更多
关键词 Wastewater treatment plants (WWTPs) Excitation-emission matrix (EEM) Parallel factor (PARAFAC) Parallel factor framework-clustering analysis (PFFCA)
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