Environmental Science and Pollution Research

, Volume 26, Issue 5, pp 5083–5093 | Cite as

Modeling and performance improvement of an anaerobic–anoxic/nitrifying-induced crystallization process via the multi-objective optimization method

  • Hongliang Dai
  • Wenliang Chen
  • Lihong Peng
  • Xingang WangEmail author
  • Xiwu LuEmail author
Research Article


The trade-off between energy savings and emission reductions of an activated sludge process is a multi-objective problem relating to several potentially conflicting objectives. Therefore, the optimal modification of an anaerobic–anoxic/nitrifying/induced crystallization (A2N-IC) process by multi-objective optimization method was studied in this work. The multi-objective optimization model comprised three evaluative indices, (effluent quality (EQ), operation cost (OC), and total volume (TV) of structures), and 14 process parameters (decision variables) solving by non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB. The trade-off relationships among EQ, OC, and TV were investigated under 30 days of dynamic influent with different constraint conditions. A series of Pareto solutions were obtained, and one Pareto solution was selected for further analysis. Results showed improved effluent concentrations of chemical oxygen demand (COD), total nitrogen (TN), ammonia-nitrogen (NH4+-N), and total phosphorous (TP) under the optimized strategy compared to the original strategy, where the average effluent concentrations decreased by 2.22, 0.47, 0.13, and 0.02 mg/L, respectively. The values of EQ and OC decreased from 0.015 kg/day and 0.15 ¥/m3 to 0.0023 kg/day and 0.12 ¥/m3, respectively, while the TV increased from 0.31 to 0.33 m3. These results indicated that the multi-objective optimization method is useful for modifying activated sludge processes.


Multi-objective optimization Energy-saving and emission-reduction Denitrifying phosphorus removal Phosphorus recovery 



This research has been supported by the Major Science and Technology Project of Water Pollution Control and Management in China (No. 2017ZX07202004-002), the National Science and Technology Support Program in China (No. 2015BAL01B01), the Social Development Project of Zhenjiang (No. 2016014), and the Natural Science Foundation of China (No. 31400448). We thank the anonymous reviewers for their constructive comments that improved the manuscript. The English in this document has been checked by at least two professional editors, both native speakers of English. For a certificate, please see


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Environmental and Chemical EngineeringJiangsu University of Science and TechnologyZhenjiangPeople’s Republic of China
  2. 2.School of Energy and EnvironmentSoutheast UniversityNanjingPeople’s Republic of China

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