Low-carbon wastewater treatment and resource recovery of recirculating aquaculture system by immobilized chlorella vulgaris based on machine learning optimization.
Bioresour Technol
; 408: 131208, 2024 Sep.
Article
em En
| MEDLINE
| ID: mdl-39098355
ABSTRACT
Immobilized microalgae biotechnologies can conserve water and space by low-carbon wastewater treatment and resource recovery in a recirculating aquaculture system (RAS). However, technical process parameters have been unoptimized considering the mutual interaction between factors. In this study, machine learning optimized the parameters of alginate-immobilized Chlorella vulgaris (C. vulgaris), that is, 474 µmol/(m2·s) of light intensity, 23 × 106 cells/mL for initial cell number, and 2.07 mm particle size. Importantly, under continuous illumination, the immobilized C. vulgaris and microalgal-bacterial consortium improved water purification and biomass reutilization. Transcriptomics of C. vulgaris showed enhanced nitrogen removal by increasing pyridine nucleotide and lipid accumulation via enhanced triacylglycerol synthesis. Symbiotic bacteria upregulated genes for nitrate reduction and organic matter degradation, which stimulated biomass accumulation through CO2 fixation and starch synthesis. The recoverable microalgae (1.94 g/L biomass, 47 % protein, 26.23 % lipids), struvite (64.79 % phosphorus), and alginate (79.52 %) every two weeks demonstrates a low-carbon resource recovery in RAS.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Carbono
/
Aquicultura
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Purificação da Água
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Biomassa
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Chlorella vulgaris
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Alginatos
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Águas Residuárias
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Aprendizado de Máquina
Idioma:
En
Revista:
Bioresour Technol
Assunto da revista:
ENGENHARIA BIOMEDICA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China