资源回收
污水处理
废水
生化工程
资源(消歧)
污染物
环境科学
范围(计算机科学)
计算机科学
环境工程
生态学
生物
工程类
计算机网络
程序设计语言
作者
Heng Wu,Anjie Li,Huaiwen Zhang,Sicong Gao,Suqi Li,Jindou Cai,Ruixiao Yan,Zhilin Xing
出处
期刊:Chemosphere
[Elsevier BV]
日期:2023-06-18
卷期号:336: 139235-139235
被引量:18
标识
DOI:10.1016/j.chemosphere.2023.139235
摘要
Swine wastewater is highly polluted with complex and harmful substances that require effective treatment to minimize environmental damage. There are three commonly used biological technologies for treating swine wastewater: conventional biological technology (CBT), microbial electrochemical technology (MET), and microalgae technology (MT). However, there is a lack of comparison among these technologies and a lack of understanding of their unique advantages and efficient operation strategies. This review aims to compare and contrast the characteristics, influencing factors, improvement methods, and microbial mechanisms of each technology. CBT is cost-effective but has low resource recovery efficiency, while MET and MT have the highest potential for resource recovery. However, all three technologies are affected by various factors and toxic substances such as heavy metals and antibiotics. Improved methods include exogenous/endogenous enhancement, series reactor operation, algal-bacterial symbiosis system construction, etc. Though MET is limited by construction costs, CBT and MT have practical applications. While swine wastewater treatment processes have developed automatic control systems, the application need further promotion. Furthermore, key functional microorganisms involved in CBT's pollutant removal or transformation have been detected, as have related genes. The unique electroactive microbial cooperation mode and symbiotic mode of MET and MT were also revealed, respectively. Importantly, the future research should focus on broadening the scope and scale of engineering applications, preventing and controlling emerging pollutants, improving automated management level, focusing on microbial synergistic metabolism, enhancing resource recovery performance, and building a circular economy based on low-cost and resource utilization.
科研通智能强力驱动
Strongly Powered by AbleSci AI