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Jiyuan Li, Jie Zhou, Wenping Cao, Ming Zhang +5
This study optimizes ammonia nitrogen (NH₄⁺-N) and phosphorus (TP) removal in a two-chamber microbial fuel cell using response surface methodology (RSM) with central composite design (CCD). Operating parameters—hydraulic retention time (HRT) and initial ammonia concentration—were systematically varied to develop predictive models. Optimal conditions achieved 94.88% NH₄⁺-N and 59.39% TP removal rates. Microbial community analysis revealed that optimization reduced species richness but strengthened dominant nitrifying and phosphorus-removing taxa, demonstrating parameter-driven community selection.
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In order to study the effects of operating conditions on the performance of a microbial fuel cell (MFC) for treating ammonia nitrogen (NH4+-N) and phosphate and the changes in the microbial community under optimized conditions, in this study, the response surface method (RSM) and central composite design (CCD) were used to carry out experiments and construct a model of the system to analyze the influence of the hydraulic retention time (HRT) and initial influent ammonia concentration on NH4+-N and the total phosphorus (TP) removal performance of the MFC, and the changes in the microbial community structure were analyzed. The results showed that: (1) the initial influent ammonia concentration had a greater impact than the HRT; (2) after optimizing the reaction conditions, the actual removal rates of NH4+-N and TP of the system were 94.88% and 59.39% (the predicted values were 90.18% and 56.25%), respectively; and (3) the total number of species in the optimization group decreased, and the richness of the microbial community decreased. The system conducted the orthoselection of the microbial community and optimized the structure of the microbial community. After the optimization, the dominant strains for ammonia and phosphorus removal on the cathode reactor of each system were strengthened at the phylum and genus levels. Under the coaction of the dominant strains, the efficiencies of nitrogen removal and phosphorus removal in the reactor were significantly improved. The performance optimization of and microbial community change in NH4+-N and TP removal in the MFC system were studied using RSM, which was helpful to improve the effect of nitrogen and phosphorus removal.