Virginia Tech
Balancing Bromate Formation, Organics Oxidation, and Pathogen Inactivation: The Impact of Bromate Suppression Techniques on Ozonation System Performance in Reuse Waters
Abstract
dc:description.abstractOzonation is an integral process in ozone-biofiltration treatment systems and is beginning to be widely adopted worldwide for water reuse applications. Ozone is effective for pathogenic inactivation and organics oxidation: both increasing assimilable organic carbon for biofiltration and eliminating trace organic contaminants which may pose a threat to human health. However, ozone can also form disinfection byproducts such as bromate from the oxidation of naturally occurring anion bromide. Bromate is a known human carcinogen and is regulated by the EU, WHO, and USEPA to a maximum limit of 10µg/L. In waters high in bromide, especially above 100µg/L, bromate formation becomes a major concern. In the secondary wastewater effluent studied, bromide concentration may exceed 500µg/L. Several bromate suppression techniques have been devised in previous work, including free ammonia addition, monochloramination, and the chlorine-ammonia process. While free ammonia addition was not found to adequately reduce bromate formation below the required MCL, monochloramine addition and the chlorine-ammonia process were found to be effective. However, the impact of these chemical suppression techniques on organics oxidation and disinfection has not been fully studied. This study explored the impact of these bromate suppression techniques at a wide range of ozone doses on bromate formation, pathogenic inactivation, ozone-refractory organics oxidation through the surrogate 1,4-dioxane, and N-nitrosodimethylamine (NDMA) formation. Additionally, bromate suppression mechanisms of monochloramine were explored further through a variety of different water quality parameters, such as through hydroxyl radical exposure and ultraviolet absorption spectrum measurements, which were correlated and utilized to develop a hydroxyl radical exposure predictive model.
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Environmental Engineering
- Department dc:contributor.department
- Environmental Science and Engineering
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2019
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Buehlmann, Peter Hamilton
- Chairs dc:contributor.committeechair
-
- Pruden, Amy
- Novak, John T.
- Committee member dc:contributor.committeemember
-
- Bott, Charles B.
Subjects
dc:subject × 5Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:22099
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/93530