Removal of natural organic matter (NOM) in biofilters can be affected by many factors including NOM characteristics, use of pre-ozonation, water temperature, and biofilter backwashing. Laboratory experiments were performed and a biofilter simulation model was developed for the purpose of evaluating the effects of each of these factors on NOM removal in biofilters. Four sources of NOM were used in this study to represent a broad spectrum of NOM types that may be encountered in water treatment. In batch experiments with raw NOM, the removal of organic carbon by biodegradation was inversely proportional to the UV absorbance (254 nm)-to-TOC ratio and directly proportional to the percentage of low molecular weight material (as determined by ultrafiltration). The extent and rate of total organic carbon (TOC) removal typically increased as ozone dose increased, but the effects were highly dependent on NOM characteristics. NOM with a higher percentage of high molecular weight material experienced the greatest enhancement in biodegradability by ozonation. The performance of laboratory-scale continuous-flow biofilters was not significantly affected by periodic backwashing, because backwashing was unable to remove large amounts of biomass from the filter media. Model simulations confirmed our experimental results and the model was used to further evaluate the effects of temperature and backwashing on biofilter performance.
|Original language||English (US)|
|Number of pages||7|
|Journal||Water Science and Technology|
|State||Published - 1999|
|Event||Proceedings of the 1999 IAWQ-IWSA International Conference on 'Removal of Humic Substances from Water' - Trondheim, Norway|
Duration: Jun 24 1999 → Jun 26 1999
Bibliographical noteFunding Information:
The authors acknowledge the financial support provided by the American Water Works Association (AWWA) through the Abel Wolman Doctoral Fellowship Program and by the AWWA Research Foundation for Project 252. The authors also acknowledge the helpful comments Project 252 including Peter Huck, Brad Coffey, Appiah Amirtharajah, Monica Emelko, and Daniel Urfer.
- Natural organic matter
- Simulation model