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Updated: Nov 1, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
Published on: April 8, 2020
Predictive modeling of haloacetonitriles under uniform formation conditions
Gamze Ersan1, Mahmut S Ersan2, Amer Kanan3
1Department of Environmental Engineering and Earth Sciences, Clemson University, Anderson, SC, 29625, United States.
Abstract:
The objective of this study was to develop models to predict the formation of HANs under uniform formation conditions (UFC) in chlorinated, choraminated, and perchlorinated/chloraminated waters of different origins. Model equations were developed using multiple linear regression analysis to predict the formation of dichloroacetonitrile (DCAN), HAN4 (trichloroacetonitrile [TCAN], DCAN, bromochloroacetonitrile [BCAN], and dibromoacetonitrile [DBAN]) and HAN6 (HAN4 plus monochloroacetonitrile, monobromoacetonitrile). The independent variables covered a wide range of values, and included ultraviolet absorbance,(UV254) dissolved organic carbon (DOC), dissolved organic nitrogen (DON), specific UV absorbance at 254 (SUVA254), bromide (Br-), pH, oxidant dose, contact time, and temperature. The regression coefficients (r2) of HAN4 and HAN6 models for natural organic matter (NOM), algal organic matter (AOM), and effluent organic matter (EfOM) impacted waters were within the range of 60-88%, while the r2 values of HAN4 and DCAN models for both groundwater and distribution systems were lower, in the range of 41-66%. The r2 values for the DCAN model were mostly higher in the individual types as compared to the cumulative analysis of all source water data together. This was attributed to differences in HAN precursor characteristics. For chlorination, among all variables, pH was found to be the most significant descriptor in the model equations describing the formation of DCAN, HAN4, and HAN6, and it was negatively correlated with HAN formation in the distribution system, groundwater, AOM, and NOM samples, while it showed an inverse relationship with HAN6 formation in EfOM impacted waters. During chloramination, pH was the most influential model descriptor for DCAN formation in the NOM. Prechlorination dose was the most predominant parameter for prechlorination/chloramination, and it was positively correlated with HAN4 formation in AOM impacted waters.
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