废水
污水处理
环境科学
废物管理
生化工程
环境工程
工程类
作者
Shengnan Chen,Jiashuo Wang,Xin Feng,Fangchao Zhao
出处
期刊:Water
[MDPI AG]
日期:2025-05-29
卷期号:17 (11): 1647-1647
被引量:1
摘要
This review systematically examines the critical mechanisms and process optimization strategies of algal–bacterial granular sludge (ABGS) technology in wastewater treatment. The key findings highlight the following: (1) enhanced pollutant removal—ABGS achieves >90% COD removal, >80% total nitrogen elimination via nitrification–denitrification coupling, and 70–95% phosphorus uptake through polyphosphate-accumulating organisms (PAOs), with simultaneous adsorption of heavy metals (e.g., Cu2+, Pb2+) via EPS binding; (2) energy-saving advantages—microalgal oxygen production reduces aeration energy consumption by 30–50% compared to conventional activated sludge, while the granular stability maintains >85% biomass retention under hydraulic shocks; (3) AI-driven optimization—machine learning models enable real-time prediction of nutrient removal efficiency (±5% error) by correlating microbial composition (e.g., Nitrosomonas abundance) with operational parameters (DO: 2–4 mg/L, pH: 7.5–8.5). This review further identifies EPS-mediated microbial co-aggregation and Chlorella–Pseudomonas cross-feeding as pivotal for system resilience. These advances position ABGS as a sustainable solution for low-carbon wastewater treatment, although challenges persist in scaling photobioreactors and maintaining symbiosis under fluctuating industrial loads.
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