An integrated monitoring system for disaster-causing organisms in the water intake areas of coastal nuclear power plants

被引:1
|
作者
Li, Chao [1 ,2 ,3 ]
Huo, Jian-ling [1 ,2 ,3 ]
Song, Yu-ze [1 ,2 ,3 ]
Yang, Lei [1 ,2 ,3 ]
Liu, Song-tang [1 ,2 ,3 ]
机构
[1] Natl Ocean Technol Ctr, Offshore Observat Dept, Tianjin, Peoples R China
[2] Minist Nat Resources, Key Lab Marine Ecol Monitoring & Restorat Technol, Shanghai, Peoples R China
[3] Minist Nat Resources, Key Lab Ocean Observat Technol, Tianjin, Peoples R China
关键词
nuclear power plant; water intake; disaster-causing organism; monitoring system; abundance estimation; optical microscopic imager; DESIGN;
D O I
10.3389/fmars.2022.1089699
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Nowadays, nuclear power plays an important role in the energy structure of many countries. However, A bloom of a disaster-causing organism (DCO) in the cold-water intake area of a coastal nuclear power plant can block the water cooling system and seriously affect the operational safety of the nuclear power unit. Currently, the traditional method of protection is to estimate the DCO abundance by regular manual investigation and sampling, but that method cannot give continuous real-time data. Instead, proposed and implemented here is a seafloor in situ integrated monitoring system for DCOs (known as IMSDCO), which is equipped with an optical microscopic imager (OMI) and hydrometric sensors to monitor automatically the DCO abundance and hydrology. All the data are transmitted to a terminal in the shore station through a photoelectric composite cable for real-time display. When the DCO abundance reaches a preset threshold, software automatically raises an alarm. Since placing IMSDCO at the cold-water intake of the Changjiang nuclear power plant, a six-month field trial has been completed, during which large amounts of hydrology data and DCO images were obtained. IMSDCO successfully identified and estimated the abundances of various DCOs (e.g., Phaeocystis globosa, Acetes chinensis, and small fish) and predicted their movements based on hydrology data. Based on the analysis of the experimental data, we discussed the reasons for the error in the abundance estimation of DCO and the methods to reduce the error. The experimental results show that the OMI-based IMSDCO can monitor and give early warning of DCOs in the water intake areas of costal nuclear power plants and is worthy of long-term deployment.
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页数:12
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