MODELING AS A TOOL FOR INVESTIGATING IFAS PROCESSES
Authors: Maas, Carol L.A.; Legge, Raymond L.; Parker, Wayne J.
Source: Proceedings of the Water Environment Federation, WEFTEC 2005: Session 71 through Session 80 , pp. 6266-6289(24)
Publisher: Water Environment Federation
Abstract:Utilization of biomass carriers for upgrading existing plants has been receiving increased attention in recent years and has resulted in a growing body of literature. In this study, data sets generated from operational integrated fixed film/activated sludge (IFAS) and fluidized fixed film systems (FFFR) systems reported in the literature were used to assess a model's representation of fundamental outcomes. Three plants were employed for the study: the Waterdown STP (IFAS), the Moorhead WWTF (FFFR) and Royal Roads University Pilot Plant (FFFR).
The impact of process variables on performance was evaluated by modifying operational and influent parameters in the model such as SRT, temperature, dissolved oxygen, BOD and TKN (using default model parameters) and comparing the results to reported findings. Similarly, the effect of calibration parameters was evaluated by modifying each parameter considered and recording output nitrification rates.
The model accurately predicted the average improvement in nitrification efficiency observed following an upgrade to IFAS in the Waterdown STP at default model parameters. Model predictions of effluent ammonia in a separate stage nitrification FFFR were also within two standard deviations of reported average summer and winter monthly conditions. Trends such as increases in nitrification rate with D.O. and decreases in nitrification rate with reduced temperature and elevated organic loading rate were established by the model. The three calibration parameters tested: Lmax; reduction in diffusion in the biofilm; and liquid film thickness; all had significant consequences for nitrification rates. Influent characterization was found to have the potential to significantly affect nitrification rates in FFFR's.
The predicted results (employing default parameters) corresponded well to available published results, considering the variability in the operational parameters. The model predicted nitrification rates to within 2–9% of the observed means. The model tended to predict lower than observed impacts of D.O. and organic surface loading rate on nitrification rates. Model results for Lmax less than the default value of 0.50 mm tended to further reduce the dependence of nitrification rates on the above noted variables and underestimate nitrification rates. Further research to refine default calibration parameters that can both simulate a reasonable biomass in the system and match observations would therefore prove useful.
Document Type: Research Article
Publication date: 2005-01-01
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