Scale and process design for sewage treatment plants in airports using multi-objective optimization model with uncertain influent concentration

  • Liming Yao
  • Linhuan He
  • Xudong ChenEmail author
Research Article


The treatment of airport sewage has posed many novel challenges because of its huge impact on the surrounding environment. This paper proposes a multi-objective decision model to optimize the scale design and process selection of sewage treatment plants in airports. In this model, we consider the conflict among the process cost, environmental protection, and benefits of recycled water. In addition, the uncertainty in influent concentration and passenger throughput is also incorporated. Airport sewage treatment has its own unique features, such as the concentration of airport sewage is higher than that of ordinary urban sewage, the change in passenger throughput impacts the volume of the airport sewage treatment, and the utilization rate of the entire sewage treatment plant must be higher than or equal to 70%. Only in this case can the airport sewage treatment plant pass the acceptance test. The Tianfu International Airport, the largest civil transportation hub airport project in southwestern China, is used to prove the efficiency of the proposed model. Finally, some significant insights are suggested for the design of wastewater treatment plants in airports.


Process selection Wastewater treatment plant of airport Multi-objective optimization Uncertainty 


Funding information

This research is supported by the National Natural Science Foundation of China (Grant No. 71771157, 71301109), Soft Science Program of Sichuan Province (Grant No. 2017ZR0154), Funding of Sichuan University (Grant No. skqx201726), China Postdoctoral Science Foundation Funded Project (Grant No. 184089, 2017M610609). Thanks for the support of Mr. Chai, an engineer of the Chengdu Shuangliu International Airport Wastewater Treatment Plant.

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflict of interest.

Supplementary material

11356_2019_4622_MOESM1_ESM.pdf (27 kb)
ESM 1 (PDF 27 kb)


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Copyright information

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

Authors and Affiliations

  1. 1.Business SchoolSichuan UniversityChengduChina

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