AIMC Topic: Chloramines

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Regression model and artificial neural network model to predict halonitromethane formation from amino acids during UV/monochloramine disinfection in bromide-containing real water.

Environmental pollution (Barking, Essex : 1987)
Halonitromethanes (HNMs) were high-toxicity nitrogenous disinfection byproducts generated by amino acids (AAs) during UV/monochloramine (UV/NHCl) disinfection in bromide-containing water. HNM concentrations fell over time, highlighting disinfection t...

Enhanced iodinated disinfection byproducts formation in iodide/iodate-containing water undergoing UV-chloramine sequential disinfection: Machine learning-aided identification of reaction mechanisms.

Water research
Restricted to the complex nature of dissolved organic matter (DOM) in various aquatic environments, the mechanisms of enhanced iodinated disinfection byproducts (I-DBPs) formation in water containing both I and IO (designated as I/IO in this study) d...

Probing nitro(so) and chloro byproducts and their precursors in natural organic matter during UV/NHCl treatment by FT-ICR MS with machine learning insights.

Water research
The UV/monochloramine (UV/NHCl) process, while efficiently eliminating micropollutants, produces toxic byproducts. This study utilized Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to investigate molecular-level changes in n...

Machine learning-guided prediction of chlorinated/chloraminated disinfection by-product formation in drinking water treatment.

Water research
Chlorination and chloramination as common water disinfection methods are challenged by the unintended formations of hazardous disinfection by-products (DBPs). Accurately predicting DBP formation is essential for improving water treatment processes an...