Modification of the activated sludge model for chemical dosage

Abstract

Full-scale experiments have been carried out to adapt the activated sludge model ASM2d to include the influence of metal dosage (Fe³⁺ and Al³⁺) for phosphorus removal. Phosphorus removal rates, nitrification rates, as well as pH and sludge settling performance, were evaluated as functions of the metal dosages. Furthermore, models relating certain parameters to the dosage of chemicals have been derived. Corresponding parameters in the ASM2d and the secondary settler models, included in the Benchmark Simulation Model No 1 (BSM1), have been modified to take the metal influence into consideration. Based on the effluent limits and penalty policy of China, an equivalent evaluation method was derived for the total cost assessment. A large number of 300-day steady-state and 14-day open-loop dynamic simulations were performed to demonstrate the difference in behavior between the original and the modified BSM1. The results show that 1) both in low and high mole concentrations, Fe³⁺ addition results in a higher phosphorus removal rate than Al³⁺; 2) the sludge settling velocity will increase due to the metal addition; 3) the respiration rate of the activated sludge is decreased more by the dosage of Al³⁺ than Fe³⁺; 4) the inhibition of Al³⁺ on the nitrification rate is stronger than that of Fe³⁺; 5) the total operating cost will reach the minimum point for smaller dosages of Fe³⁺, but always increase with Al³⁺ addition.

Keywords

activated sludge model / chemical precipitation / benchmark simulation model / phosphorus removal / respiratory rate / sludge settling

References

[1] Henze M, Gujer W, Mino T, van Loosdrecht M. Activated Sludge Models ASM1, ASM2, ASM2d and ASM3. IWA Task Group on Mathematical Modelling for Design and Operation of Biological Wastewater Treatment, IAWPRC Scientific and Technical Reports No. 9. London: IWA Publishing, 2000

[2] Batstone D J, Keller J, Angelidaki I, Kalyuzhnyi S V, Pavlostathis S G, Rozzi A, Sanders W T M, Siegrist H, Vavilin V A. The IWA Anaerobic Digestion Model No 1 (ADM1). Water Science & Technology, 2002, 45(10): 65–73

[3] Jeppsson U, Alex J, Batstone D J, Benedetti L, Comas J, Copp J B, Corominas L, Flores-Alsina X, Gernaey K V, Nopens I, Pons M N, Rodríguez-Roda I, Rosen C, Steyer J P, Vanrolleghem P A, Volcke E I P, Vrecko D. Benchmark simulation models, quo vadis? Water Science & Technology, 2013, 68(1): 1–15

[4] Olsson G. ICA and me—A subjective review. Water Research, 2012, 46(6): 1585–1624

[5] Shen W, Chen X, Corriou J P. Application of model predictive control to the BSM1 benchmark of wastewater treatment process. Computers & Chemical Engineering, 2008, 32(12): 2849–2856

[6] Corriou J P, Pons M N. Model predictive control of wastewater treatment plants: Application to the BSM1 benchmark. Computer Aided Chemical Engineering, 2004, 18: 625–630

[7] Stare A, Vrecko D, Hvala N, Strmcnik S. Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: a simulation study. Water Research, 2007, 41(9): 2004–2014

[8] Vreck D, Gernaey K V, Rosen C, Jeppsson U. Benchmark simulation Model no 2 in Matlab-simulink: towards plant-wide WWTP control strategy evaluation. Water Science & Technology, 2006, 54(8): 65–72

[9] Maere T, Verrecht B, Moerenhout S, Judd S, Nopens I. BSM-MBR: a benchmark simulation model to compare control and operational strategies for membrane bioreactors. Water Research, 2011, 45(6): 2181–2190

[10] Gernaey K V, Jorgensen S B. Benchmarking combined biological phosphorus and nitrogen removal wastewater treatment processes. Control Engineering Practice, 2004, 12(3): 357–37310.1016/S0967-0661(03)00080-7

[11] Guo G, Wang Y, Wang C, Wang H, Pan M, Chen S. Short-term effects of excessive anaerobic reaction time on anaerobic metabolism of denitrifying polyphosphate-accumulating organisms linked to phosphorus removal and N₂O production. Frontiers of Environmental Science & Engineering, 2013, 7(4): 616–624

[12] Ma B, Wang S, Zhu G, Ge S, Wang J, Ren N, Peng Y. Denitrification and phosphorus uptake by DPAOs using nitrite as an electron acceptor by step-feed strategies. Frontiers of Environmental Science & Engineering, 2013, 7(2): 267–272

[13] Shijian G, Yongzhen P, Congcong L, Shuying W. Practical consideration for design and optimization of the step feed process. Frontiers of Environmental Science & Engineering, 2013, 7(1): 135–142

[14] Cao G, Wang S, Peng Y, Miao Z. Biological nutrient removal by applying modified four step-feed technology to treat weak wastewater. Bioresource Technology, 2013, 128(0): 604–611

[15] Zhang Z, Li Y, Wei L, Lü Y, Wang M, Gao B. Effect of ferric chloride on the properties of biological sludge in co-precipitation phosphorus removal process. Chinese Journal of Chemical Engineering, 2013, 21(5): 564–568

[16] Zhaoxu P, Yongzhen P, Zhenbo Y, Xuliang L, Xiaoling L, Randeng W. Control of sludge settleability and nitrogen removal under low dissolved oxygen condition. Frontiers of Environmental Science and Engineering, 2012, 6(6): 884–891

[17] Henze M, Gujer W, Mino T, Matsuo T, Wentzel M C, Marais G V R, Van Loosdrecht M C M. Activated Sludge Model No.2d, ASM2d. Water Science & Technology, 1999, 39(1): 165–182

[18] Liu Y, Shi H, Li W, Hou Y, He M. Inhibition of chemical dose in biological phosphorus and nitrogen removal in simultaneous chemical precipitation for phosphorus removal. Bioresource Technology, 2011, 102(5): 4008–4012

[19] Liwarska-Bizukojc E, Bizukojc M. A new approach to determine the kinetic parameters for nitrifying microorganisms in the activated sludge systems. Bioresource Technology, 2012, 109(0): 21–25

[20] Akça L, Kinaci C, Karpuzcu M. A model for optimum design of activated sludge plants. Water Research, 1993, 27(9): 1461–1468

[21] Takacs I, Patry G G, Nolasco D. A dynamic-model of the clarification thickening process. Water Research, 1991, 25(10): 1263–1271

[22] Gernaey K V, Jeppsson U, Batstone D J, Ingildsen P. Impact of reactive settler models on simulated WWTP performance. Water Science & Technology, 2006, 53(1): 159–167

[23] Ostace G S, Baeza J A, Guerrero J, Guisasola A, Cristea V M, Agachi P S, Lafuente J. Development and economic assessment of different WWTP control strategies for optimal simultaneous removal of carbon, nitrogen and phosphorus. Computers & Chemical Engineering, 2013, 53: 164–177

[24] Vanrolleghem P A, Gillot S. Robustness and economic measures as control benchmark performance criteria. Water Science & Technology, 2002, 45(4-5): 117–126

[25] Yang L, Zeng S, Chen J, He M, Yang W. Operational energy performance assessment system of municipal wastewater treatment plants. Water Science & Technology, 2010, 62(6): 1361–1370

[26] Yu F, Niu K Y, Cao D, Wang J N. Design for a municipal wastewater treatment charge standard system based on cost accounting. China Environmental Science, 2011, 31(9): 1578–1584

[27] Vanrolleghem P A, Jeppsson U, Carstensen J, Carlsson B, Olsson G. Integration of wastewater treatment plant design and operation－A systematic approach using cost functions. Water Science & Technology, 1996, 34(3-4): 159–171

Acknowledgements

The authors are particularly indebted to Prof. Ulf Jeppsson, Lund University, Sweden and Prof. Krist V. Gernaey, Danish Technical University, Denmark. They have produced the modeling framework for the BSM models. Prof. Jeppsson has also generously provided software that has been the basis of this work and has given constructive feedback to the results.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg