Using machine learning to trace the pollution sources of disinfection by-products precursors compared to receptor models

Xiao, Yuan; Ma, Shunjun; Yang, Shumin; He, Huan; He, Xin; Li, Cheng; Feng, Yuheng; Xu, Bin; Tang, Yulin

doi:10.1016/j.scitotenv.2023.169671

Cited by 3 publications

(1 citation statement)

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“…Due to these reasons, PARAFAC is the most employed algorithm to analyse fluorescent organic matter within water treatment plants; the information about cases of application can be find elsewhere [16][17][18]. Currently, EEM-PARAFAC is still gaining momentum with its application with DOM real-time continuous monitoring [19][20][21], combination with machine learning [22,23], or even its detection of fluorescent emerging contaminants in wastewater effluents [24]. In this sense, our group has thoroughly explored, with success, the use of EEM-PARAFAC to visualise oxidative changes in fluoroquinolones (antibiotics), also being able to track the formation of fluorescent oxidation by-products and estimate its molecular structure [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Dissolved Organic Matter Behaviour by Conventional Treatments of a Drinking Water Plant: Controlling Its Changes with EEM-PARAFAC

Sciscenko,

Binetti,

Escudero-Oñate

et al. 2024

Applied Sciences

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In the last 20 years, several articles related to the use of fluorescence excitation–emission matrices—parallel factor analysis (EEM-PARAFAC) to monitor dissolved organic matter (DOM) in drinking- and wastewater treatment plants were published. Noteworthy, its use in respective quality control laboratories remains scarce. To extend its popularisation, in this work, EEM-PARAFAC was employed to analyse the DOM composition changes along the different stages of the drinking water treatment plant administrated by Società Metropolitana Acque Torino. The best PARAFAC model was the one of three components, indicating that the Po River is constituted, mainly, by humic acid-like (HA-L) and tryptophan-like (Try-L) substances, the tyrosine-like ones being negligible (Tyr-L). Results indicated that physical treatments (sedimentation) did not produce a reduction in the PARAFAC scores; however, a 50% decay in 254 nm absorbance was observed. Fluorescent DOM was only removed with chemical treatments, obtaining ca. 70% HA-L scores decay with ozonation and 40% with chlorination. Furthermore, although ozonation degraded HA-L substances, the Try-L scores increased by 25%, indicating the transformation of HA-L into smaller molecules. On the contrary, total organic carbon measurements only exhibited a significant change when comparing the treatment plant’s inlet and outlet (approximately a 45% decrease), but not within intermediate processes.

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