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Model-based evaluation of a new upgrading concept for N-removal
S Salem1, D Berends, J J Heijnen
1Kluyver Laboratory for Biotechnology, Delft University of Technology, The Netherlands.
Summary
Mathematical modeling shows bio-augmentation in wastewater treatment can significantly reduce plant volume expansion needs. This approach enhances nitrification, cutting costs and time compared to conventional upgrades.
Area of Science:
- Environmental Engineering
- Wastewater Treatment Technologies
- Biotechnology
Background:
- Mathematical modeling is crucial for evaluating new wastewater treatment concepts, bridging lab-scale findings to full-scale applications.
- Bio-augmentation can achieve nitrification in activated sludge systems even with limited aerobic sludge retention time.
- Augmenting the endogenous nitrifying population is a key strategy for improving wastewater treatment efficiency.
Purpose of the Study:
- To evaluate the potential of bio-augmentation for enhancing nitrification in wastewater treatment plants.
- To assess a novel concept of implementing a nitrification reactor in the sludge return line.
- To compare the efficacy of bio-augmentation against conventional plant expansion using mathematical modeling.
Main Methods:
- Development of a mathematical model based on the TUDP model, implemented in AQUASIM.
- Application of the model to an existing wastewater treatment plant (WWTP Walcheren, The Netherlands) requiring upgrades.
- Comparative analysis of bio-augmentation versus extending existing aeration and anoxic tanks.
Main Results:
- Bio-augmentation in the return sludge line required only a 75% increase in total tank volume, including side stream tanks.
- Conventional extension of aeration basins and anoxic tanks necessitated a 225% volume increase.
- Modeling results provided a quantitative basis for evaluating the benefits of the bio-augmentation system.
Conclusions:
- Bio-augmentation in the return sludge line is a highly effective and space-saving strategy for upgrading wastewater treatment plants.
- Mathematical modeling enabled a confident decision for full-scale implementation, significantly reducing the scale-up period.
- This approach offers substantial cost and time savings compared to traditional expansion methods.