Modeling and optimization of an algal-based sewage treatment and resource recovery (STaRR) system

Abstract

This paper presents modeling and optimization of an algal-based sewage treatment and resource recovery (STaRR) system composed of the following subprocesses: S,1) mixotrophic algal sewage treatment; S,2) hydrothermal liquefaction (HTL) of the resulting algal biomass; S,3) phosphorus recovery from the solid HTL char via leaching and precipitation; and S,4) nitrogen recovery from the HTL aqueous phase via a gas-permeable membrane (GPM). Specific models for the above subprocesses have been developed and validated in previous studies. Here, those models are integrated to optimize the STaRR system based on operating cost and profit to reduce wastewater treatment costs. The following operational conditions were identified as optimal for the STaRR system: 1) fed-batch cycle time of 3 d for S,1; 2) temperature of 350 °C, process time of 1 h, and biomass content of 20 wt% for S,2; 3) temperature of 60 °C, process time of 72 h, alkali concentration of 0.5 M NaOH, alkali eluent-to-char (L:S) ratio of 20 with mixing at 20 rpm to recover calcium phosphate in S,3; and 4) process time of 70 h and a membrane area:feed volume ratio of 2.32 m2/m3 for S,4. Under these optimal conditions, the STaRR system incurred 20% lower operating costs than the pre-optimization version with a different P recovery process and without N-recovery via GPM. The optimized STaRR system recovered 69.1 ± 2.4% of P in the primary effluent as calcium phosphate and 42.9 ± 1.9% of N as ammonium sulfate at an operating cost of $0.20/m3 of primary effluent.