Kesikli biyoreaktörde evsel atıksu arıtımının ASM1 modeli ile simülasyonu ve performans değerlendirmesi

Öz

Makalede, simüle edilmiş evsel nitelikli atık suyun kesikli bir biyoreaktörde arıtımına ilişkin olarak, organik madde (KOİ), azot bileşenleri (TN, TKN, NH₄⁺-N), toplam askıda katı madde (TSS) ile kullanım hızları parametreleri (OUR, COUR, NOUR vb.) üzerindeki zamana bağlı değişimler incelenmiştir. Arıtma prosesi yalnızca aerobik fazdan oluşmakta olup, simülasyon çalışmaları Aktif Çamur Modeli No.1 (ASM1) esas alınarak gerçekleştirilmiş ve modelleme için Polymath Plus simülasyon yazılımı kullanılmıştır. Simülasyon süresince reaktördeki hidrolik kalış süresi sabit tutulmuş, KOİ/N/P oranı (100/6,99/1,46) ve VSS/TSS oranı (0,80) olacak şekilde hazırlanması sağlanmıştır. Başlangıç KOİ konsantrasyonu 597 mg/L olarak belirlenmiş ve farklı simülasyon sürelerinin arıtım performansı üzerindeki etkileri değerlendirilmiştir. Elde edilen bulgular, simülasyon süresinin artmasıyla birlikte KOİ, TN, TKN, NH₄⁺-N ve TSS giderim yüzdelerinde artış sağlandığını ve çıkış suyu kalitesinin iyileştiğini göstermiştir. En yüksek giderim verimleri yaklaşık 12,9 saatlik simülasyon süresinde elde edilmiş olup, KOİ %71,55, TN %14,72, TKN %70,75, NH₄⁺-N %99,95 ve TSS %33,72 olarak hesaplanmıştır. Bu sonuçlar, kesikli biyoreaktörlerin evsel atık su arıtımında etkili bir işletme stratejisi sunduğunu ve ASM1 modeli ile yapılan simülasyonların sistem performansının değerlendirilmesinde başarılı bir araç olduğunu ortaya koymaktadır.

Anahtar Kelimeler

• Matematiksel modelleme
• Organik madde giderimi
• Biyoreaktör
• Polymath Plus
• Nitrifikasyon

Simulation and performance evaluation of domestic wastewater treatment in batch bioreactor with ASM1 model

Öz

In this paper, the time-dependent changes in organic matter (COD), nitrogen components (TN, TKN, NH₄⁺-N), total suspended solids (TSS) and utilisation rate parameters (OUR, COUR, NOUR, etc.) for the treatment of simulated domestic wastewater in a batch bioreactor are investigated. The treatment process consists of aerobic phase only and simulation studies were carried out based on Activated Sludge Model No.1 (ASM1) and Polymath Plus simulation software was used for modelling. During the simulation period, the hydraulic residence time in the reactor was kept constant and the COD/N/P ratio (100/6.99/1.46) and VSS/TSS ratio (0.80) were maintained. The initial COD concentration was set as 597 mg/L and the effects of different simulation times on the treatment performance were evaluated. The results showed that the removal percentages of COD, TN, TKN, NH₄⁺-N and TSS increased and effluent quality improved with increasing simulation time. The highest removal efficiencies were obtained at a simulation time of approximately 12.9 hours and calculated as COD 71.55%, TN 14.72%, TKN 70.75%, NH₄⁺-N 99.95% and TSS 33.72%. These results show that batch bioreactors offer an effective operation strategy for domestic wastewater treatment and simulations with the ASM1 model are a successful tool for evaluating system performance.

Anahtar Kelimeler

• Mathematical modelling
• Organic matter removal
• Bioreactor
• Polymath Plus
• Nitrification

Kaynakça

1. Mulas, M. (2006). Modelling and control of activated sludge processes. Università degli Studi di Cagliari.
2. Gernaey, K. V., van Loosdrecht, M. C., Henze, M., Lind, M., and Jørgensen, S. B. (2004). Activated sludge wastewater treatment plant modelling and simulation: State of the art. Environmental Modelling & Software, 19(9), 763–783.
3. Rieger, L., Gillot, S., Langergraber, G., Ohtsuki, T., Shaw, A., Takacs, I., and Winkler, S. (2012). Guide to using activated sludge models. IWA Publishing.
4. Makinia, J., and Zaborowska, E. (2020). Mathematical modelling and computer simulation of activated sludge systems. IWA Publishing.
5. Henze, M., Gujer, W., Mino, T., and van Loosdrecht, M. C. M. (2000). Activated sludge models ASM1, ASM2, ASM2d, and ASM3. IWA Publishing
6. Wu, X., Yang, Y., Wu, G., Mao, J., and Zhou, T. (2016). Simulation and optimisation of coking wastewater biological treatment process with activated sludge models (ASM). Journal of Environmental Management, 165, 235–242.
7. Savun, B. (2020). On the use of mathematical models for wastewater treatment: A review and analysis of activated sludge models ASM1 and ASM3. İstanbul University.
8. Brdjanovic, D., Meijer, S. C., Lopez-Vazquez, C. M., Hooijmans, C. M., and van Loosdrecht, M. C. (Eds.). (2015). Applications of activated sludge models. IWA Publishing.

9. Van Loosdrecht, M. C. M., Lopez-Vazquez, C. M., Meijer, S. C. F., Hooijmans, C. M., and Brdjanovic, D. (2015). Twenty-five years of ASM1: Past, present, and future of wastewater treatment modelling. Journal of Hydroinformatics, 17(5), 697–718.
10. Makinia, J., and Zaborowska, E. (2019). Mathematical modelling and computer simulation of activated sludge systems. IWA Publishing.
11. Rittmann, B. E., and McCarty, P. L. (2001). Environmental biotechnology: Principles and applications. McGraw-Hill.
12. Droste, R. L., and Gehr, R. (2018). Theory and practice of water and wastewater treatment (2nd ed.). Wiley.
13. Al, R., Behera, C. R., Gernaey, K. V., and Sin, G. (2019). Towards development of a decision support tool for conceptual design of wastewater treatment plants using stochastic simulation optimization. In A. Kiss, E. Zondervan, R. Lakerveld, and L. Özkan (Eds.), Proceedings of the 29th European Symposium on Computer Aided Process Engineering (Vol. 46, pp. 325–330). Elsevier.
14. Hauduc, H., Rieger, L., Oehmen, A., Van Loosdrecht, M. C. M., Comeau, Y., Héduit, A., and Gillot, S. (2013). Critical review of activated sludge modeling: State of process knowledge, modeling concepts, and limitations. Biotechnology and Bioengineering, 110(1), 24–46.
15. Kargı, F., and Dinçer, A. R. (1997). Biological treatment of saline wastewater by fed-batch operation. Journal of Chemical Technology and Biotechnology, 69(2), 167–172.
16. Andreottola, G., Bortone, G., and Tilche, A. (1997). Experimental validation of a simulation and design model for nitrogen removal in sequencing batch reactors. Water Science and Technology, 35(1), 113–120.
17. Taşlı, R., Artan, N., and Orhon, D. (1997). The influence of different substrates on enhanced biological phosphorus removal in a sequencing batch reactor. Water Science and Technology, 35(1), 75–80.
18. Kargı, F., and Uygur, A. (2002). Nutrient removal performance of a sequencing batch reactor as a function of the sludge age. Enzyme and Microbial Technology, 31(6), 842–847.
19. Kargı, F., and Uygur, A. (2003). Nutrient removal performance of a five-step sequencing batch reactor as a function of nutrient wastewater composition. Process Biochemistry, 38(7), 1039–1045.
20. Hulsbeek, J. J., Kruit, J., Roeleveld, P. J., and van Loosdrecht, M. C. (2002). A practical protocol for dynamic modelling of activated sludge systems. Water Science and Technology, 45(6), 127–136.
21. Demoulin, G., Goronszy, I. C., Wutscher, K., and Forsthuber, E. (1997). Cocurrent nitrification/denitrification and biological P-removal in cyclic activated sludge plants by redox controlled cycle operation. Water Science and Technology, 35(1), 215–224.
22. Evans, R. W. (2012). Implementing an improved activated sludge model into modeling software, Master’s thesis, University of Regina.
23. Chen, G., van Loosdrecht, M. C. M., Ekama, G. A., and Brdjanovic, D. (2020). Biological wastewater treatment: Principles, modelling and design (2nd ed.). IWA Publishing.