TY - JOUR
T1 - One-step fluorometric determination of multiple-component dissolved organic matter in aquatic environments
AU - Gong, Bo
AU - Chen, Wei
AU - Sit, Patrick H.-L.
AU - Liu, Xian-Wei
AU - Qian, Chen
PY - 2023/5/15
Y1 - 2023/5/15
N2 - Dissolved organic matter (DOM) is ubiquitous in aqueous environments and is composed of different components that play different but important roles in the migration and the fate of pollutants, emergence of the disinfect byproduct, thus requiring quantitative characterization. However, until now, simultaneous quantification of the main contents in DOM, i.e., saccharides, proteins, and humic substances, has been difficult, impeding us from understanding and predicting the environmental behaviors of typical pollutants. In this work, a fluorescence approach based on the excitation emission matrix (EEM), combined with a new algorithm, denoted matrix reconstruction coupled with prior linear decomposition (MR-PLD), was developed to quantify multiple DOM simultaneously. First, a set of simulated water samples consisting of glucose, tryptones, and humic acid (HA) were analyzed using MR-PLD to validate the feasibility of the method. The DOM components could be reliably determined with a higher accuracy than parallel factor analysis (PARAFAC) and Parallel Factor Framework-Linear Regression (PFFLR), also with a more convenient procedure than conventional PLD. Second, both actual simulated and experimental methods were performed to test the anti-interference performance of MR-PLD, indicating that the quantification of DOM would not be significantly impacted by other fluorophores. Finally, several actual water samples from natural waters and wastewater treatment plants were also analyzed to confirm the robustness of this method in actual aqueous environments. This study provides a new approach to characterize DOM with EEM, contributing to its convenient concentration monitoring and the further exploration of the environmental impacts. © 2023 Elsevier B.V.
AB - Dissolved organic matter (DOM) is ubiquitous in aqueous environments and is composed of different components that play different but important roles in the migration and the fate of pollutants, emergence of the disinfect byproduct, thus requiring quantitative characterization. However, until now, simultaneous quantification of the main contents in DOM, i.e., saccharides, proteins, and humic substances, has been difficult, impeding us from understanding and predicting the environmental behaviors of typical pollutants. In this work, a fluorescence approach based on the excitation emission matrix (EEM), combined with a new algorithm, denoted matrix reconstruction coupled with prior linear decomposition (MR-PLD), was developed to quantify multiple DOM simultaneously. First, a set of simulated water samples consisting of glucose, tryptones, and humic acid (HA) were analyzed using MR-PLD to validate the feasibility of the method. The DOM components could be reliably determined with a higher accuracy than parallel factor analysis (PARAFAC) and Parallel Factor Framework-Linear Regression (PFFLR), also with a more convenient procedure than conventional PLD. Second, both actual simulated and experimental methods were performed to test the anti-interference performance of MR-PLD, indicating that the quantification of DOM would not be significantly impacted by other fluorophores. Finally, several actual water samples from natural waters and wastewater treatment plants were also analyzed to confirm the robustness of this method in actual aqueous environments. This study provides a new approach to characterize DOM with EEM, contributing to its convenient concentration monitoring and the further exploration of the environmental impacts. © 2023 Elsevier B.V.
KW - Dissolved organic matter
KW - Excitation emission matrix
KW - Fluorescence
KW - Matrix combination
KW - Simultaneous determination
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85148538645&origin=recordpage
U2 - 10.1016/j.scitotenv.2023.162200
DO - 10.1016/j.scitotenv.2023.162200
M3 - RGC 21 - Publication in refereed journal
C2 - 36791859
SN - 0048-9697
VL - 873
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 162200
ER -