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Strain Screening and Conditions Optimization in Microalgae-Based Monosodium Glutamate Wastewater (MSGW) Treatment
The wastewater generated from monosodium glutamate production displays distinctive features of elevated salinity, organic content, as well as nitrogen and phosphorus concentrations, and its indiscriminate disposal poses a significant threat to water quality and can cause detrimental impacts on aquatic ecosystems. The application of microalgae for monosodium glutamate wastewater (MSGW) treatment can result in simultaneous wastewater purification and biomass recovery. In this study, the algae species capable of thriving in diluted MSGW were screened, and the wastewater composition and growth conditions were optimized to obtain high algal biomass and nutrient removal rate. Among the tested species, Chlorella sp. FACHB-30 demonstrated superior potential for MSGW treatment and achieved a maximum specific growth rate of 0.28 d−1 and the highest COD removal rate of 61.50% over a 20-day cultivation period with trace metals supplementation in the wastewater. Moreover, the cultivation of Chlorella sp. FACHB-30 yielded considerable reductions in total phosphate (69.09%), total nitrogen (26.93%), and -N (51.91%) levels in the wastewater. The optimum conditions for achieving maximum algal density and highest nutrient removal were determined as light intensity of 150 μmol m−2s−1, inoculation concentration of 1 × 105 cells mL−1, and an iron concentration of 10−5 mol L−1. Finally, under the optimized conditions, the removal rates of total phosphate, total nitrogen, -N, and COD were determined to be 87.60%, 68.05%, 75.89%, and 77.96%, respectively. The findings of this study highlight the potential for enhancing the nutrient removal efficiency of microalgae-based MSGW treatment through the implementation of a combined approach that involves the selection of tolerant strains, optimization of cultivation conditions, and refinement of wastewater composition.
Strain Screening and Conditions Optimization in Microalgae-Based Monosodium Glutamate Wastewater (MSGW) Treatment
The wastewater generated from monosodium glutamate production displays distinctive features of elevated salinity, organic content, as well as nitrogen and phosphorus concentrations, and its indiscriminate disposal poses a significant threat to water quality and can cause detrimental impacts on aquatic ecosystems. The application of microalgae for monosodium glutamate wastewater (MSGW) treatment can result in simultaneous wastewater purification and biomass recovery. In this study, the algae species capable of thriving in diluted MSGW were screened, and the wastewater composition and growth conditions were optimized to obtain high algal biomass and nutrient removal rate. Among the tested species, Chlorella sp. FACHB-30 demonstrated superior potential for MSGW treatment and achieved a maximum specific growth rate of 0.28 d−1 and the highest COD removal rate of 61.50% over a 20-day cultivation period with trace metals supplementation in the wastewater. Moreover, the cultivation of Chlorella sp. FACHB-30 yielded considerable reductions in total phosphate (69.09%), total nitrogen (26.93%), and -N (51.91%) levels in the wastewater. The optimum conditions for achieving maximum algal density and highest nutrient removal were determined as light intensity of 150 μmol m−2s−1, inoculation concentration of 1 × 105 cells mL−1, and an iron concentration of 10−5 mol L−1. Finally, under the optimized conditions, the removal rates of total phosphate, total nitrogen, -N, and COD were determined to be 87.60%, 68.05%, 75.89%, and 77.96%, respectively. The findings of this study highlight the potential for enhancing the nutrient removal efficiency of microalgae-based MSGW treatment through the implementation of a combined approach that involves the selection of tolerant strains, optimization of cultivation conditions, and refinement of wastewater composition.
Strain Screening and Conditions Optimization in Microalgae-Based Monosodium Glutamate Wastewater (MSGW) Treatment
Yanmin Zhuang (Autor:in) / Qingling Su (Autor:in) / Haowen Wang (Autor:in) / Chengzong Wu (Autor:in) / Shanying Tong (Autor:in) / Jumei Zhang (Autor:in) / Hongjin Qiao (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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