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Environ Sci Technol. 2012 Jan 3;46(1):119-31. doi: 10.1021/es203312s. Epub 2011 Dec 12.

Halonitroalkanes, halonitriles, haloamides, and N-nitrosamines: a critical review of nitrogenous disinfection byproduct formation pathways.

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Department of Chemical and Environmental Engineering, Yale University, Mason Lab 313b, 9 Hillhouse Avenue, New Haven, Connecticut 06520, United States.


Interest in the formation of nitrogenous disinfection byproducts (N-DBPs) has increased because toxicological research has indicated that they are often more genotoxic, cytotoxic, or carcinogenic than many of the carbonaceous disinfection byproducts (C-DBPs) that have been a focus for previous research. Moreover, population growth has forced utilities to exploit source waters impaired by wastewater effluents or algal blooms. Both waters feature higher levels of organic nitrogen, that might serve as N-DBP precursors. Utilities are exploring new disinfectant combinations to reduce the formation of regulated trihalomethanes and haloacetic acids. As some of these new combinations may promote N-DBP formation, characterization of N-DBP formation pathways is needed. Formation pathways for halonitroalkanes, halonitriles, haloamides, and N-nitrosamines associated with chlorine, ozone, chlorine dioxide, UV, and chloramine disinfection are critically reviewed. Several important themes emerge from the review. First, the formation pathways of the N-DBP families are partially linked because most of the pathways involve similar amine precursors. Second, it is unlikely that a disinfection scheme that is free of byproduct formation will be discovered. Disinfectant combinations should be optimized to reduce the overall exposure to toxic byproducts. Third, the understanding of formation pathways should be employed to devise methods of applying disinfectants that minimize byproduct formation while accomplishing pathogen reduction goals. Fourth, the well-characterized nature of the monomers constituting the biopolymers that likely dominate the organic nitrogen precursor pool should be exploited to predict the formation of byproducts likely to form at high yields.

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