Control and remediation methods for eutrophic lakes in the past 30 years

被引:107
作者
Zhang, Yuan [1 ,2 ]
Luo, Pingping [1 ,2 ]
Zhao, Shuangfeng [2 ]
Kang, Shuxin [2 ]
Wang, Pengbo [2 ]
Zhou, Meimei [1 ,2 ]
Lyu, Jiqiang [1 ,2 ]
机构
[1] Chang'an Univ, Minist Educ, Key Lab Subsurface Hydrol & Ecol Effects Arid Reg, Xian 710064, Peoples R China
[2] Chang'an Univ, Sch Water & Environm, Xian 710064, Peoples R China
基金
国家重点研发计划;
关键词
bioremediation; eutrophication; nitrogen and phosphorus; physical and chemical techniques; SHALLOW LAKE; FLOATING-BED; WASTE-WATER; POLLUTED RIVER; ALGAL BLOOMS; RESTORATION; NITROGEN; REMOVAL; BIOFILM; PHOSPHORUS;
D O I
10.2166/wst.2020.218
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Accelerated eutrophication, which is harmful and difficult to repair, is one of the most obvious and pervasive water pollution problems in the world. In the past three decades, the management of eutrophication has undergone a transformation from simple directed algal killing, reducing endogenous nutrient concentration to multiple technologies for the restoration of lake ecosystems. This article describes the development and revolution of three remediation methods in application, namely physical, chemical, and biological methods, and it outlines their possible improvements and future directions. Physical and chemical methods have obvious and quick effects to purify water in the short term and are more suitable for small-scale lakes. However, these two methods cannot fundamentally solve the eutrophic water phenomenon due to costly and incomplete removal results. Without a sound treatment system, the chemical method easily produces secondary pollution and residues and is usually used for emergency situations. The biological method is cost-effective and sustainable, but needs a long-term period. A combination of these three management techniques can be used to synthesize short-term and long-term management strategies that control current cyanobacterial blooms and restore the ecosystem. In addition, the development and application of new technologies, such as big data and machine learning, are promising approaches.
引用
收藏
页码:1099 / 1113
页数:15
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