New advances in fluorescence excitation-emission matrix spectroscopy for the characterization of dissolved organic matter in drinking water treatment: A review

• Published in: Chemical engineering journal (Lausanne, Switzerland : 1996) Switzerland : 1996), 2020-02, Vol.381, p.122676, Article 122676
• Main Authors: Li, Lei, Wang, Yang, Zhang, Wenjun, Yu, Shuili, Wang, Xianyun, Gao, Naiyun
• Format: Article
• Language: English
• Subjects: Characterization; Dissolved organic matter; Drinking water treatment; EEM; Monitoring
• ISSN: 1385-8947; 1873-3212
• DOI: 10.1016/j.cej.2019.122676

•New advances of excitation-emission matrix interpretation methods are reported.•Findings in investigation of water works by fluorescence techniques are summarized.•Assistances from fluorescence focus on evaluation, observation and correlation.•Limitation of fluorescence characterizing organic matter are emphasized.•Failure in using fluorescence monitoring membrane filtration is pointed out. Fluorescence technology has been increasingly applied in dissolved organic matter (DOM) characterization due to its remarkable sensitivity and selectivity. Interest in using fluorescence technology to investigate drinking water treatment with a focus on coagulation, adsorption, membrane filtration and disinfection is growing. Fluorescence excitation-emission matrix (EEM) spectroscopy, also known as three-dimensional fluorescence (3D-EEM) or fluorescence fingerprinting, is one of the most predominant approaches because of the massive amount of data, visual maps and multidimensional information it provides. Various EEM map interpretation methods have been developed. This paper reviews current predominant 3D-EEM interpretation methods (ranging from basic methods, peak picking and fluorescence regional integration (FRI) to chemometric methods) and summarizes the latest findings and problems related to practical applications. The correlations between optical and physicochemical properties, such as molecular weight and hydrophilic-hydrophobic properties, are investigated. Novel findings on drinking water trains obtained with the assistance of these interpretation methods are discussed and broadly classified as follows: a) evaluating water treatment performance, b) observing DOM behavior, c) monitoring and predicting micropollutants and disinfection byproducts (DBPs). The importance of using artificial intelligence in fluorescence technology and developing advanced real-time sensors, the weaknesses of fluorescence spectroscopy and the need for combination with other technologies (e.g., fractionation techniques) are highlighted.