Nuclear Power Cooling-Water System Disaster-Causing Organisms: Outbreak and Aggregation Mechanisms, Early-warning Monitoring, Prevention and Control

Microalgae blooms are a frequent occurrence in coastal waters worldwide. It is reasonable to assume that these blooms have various influences on bacterial communities, which in turn may affect the development and dissipation of the bloom. However, the bacterial community characteristics, particularly of attached bacteria, associated with microalgae blooms remain unclear. In this study, we investigated the community profiles of bacteria using high-throughput sequencing during a Phaeocystis globosa bloom in Mirs Bay, southern China, in January 2021. Bacteria living in three habitats, i.e., bacterioplankton, particle-attached bacteria, and colony-attached bacteria, were studied from the exponential growth phase to the decline growth phase of the bloom. Distinct variations in bacterial community composition existed among the three habitats. Bacteroidota, Proteobacteria, and Cyanobacteria were the dominant phyla of bacterioplankton, particle–attached bacteria, and colony-attached bacteria, respectively. Richness and diversity were significantly highest (p < 0.01) in particle-attached bacteria, followed by bacterioplankton, and lowest in colony-attached bacteria. The community diversities of bacterioplankton and particle-attached bacteria decreased significantly (p < 0.05) as the bloom shifted from the exponential to the decline phase. During the decline growth phase of the bloom, Bacteroidota and Verrucomicrobiota were the dominant remarkably abundant bacteria in the bacterioplankton community, whereas Verrucomicrobiota was dominant in the particle-attached bacteria community. No significant difference was observed in the colony-attached bacterial community between the exponential and decline phases of the P. globosa bloom owing to their complex network. The results of this study suggest that P. globose bloom has a profound impact on marine bacteria, particularly species that can decompose organic matter, which could play a crucial role in the dissipation of algal blooms.

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.

Biofouling is one of the main factors affecting the efficiency and safety of cooling water systems in coastal nuclear power plants. Understanding the population dynamics, succession rules and cumulative effects of major fouling organisms is the basis for targeted prevention and control. A 1-year simulated concrete panel test was conducted from December 2020 to November 2021 in Xinghua Bay, China. A total of 78 species of fouling organisms were recorded by combining the monthly, seasonal, semiannual, annual and monthly cumulative panels, and the community composition was dominated by nearshore warm-water species, making for a typical subtropical inner bay-type community. The fouling organisms had a peak attachment period from June to October. Significantly more attachment was observed during summer (from June to August) than during the other three seasons. The attachment amount in the second half-year (from June to November) was much higher than that in the first half-year (from December to May). The attachment thickness, density, and biomass of the bottom summer panels reached 20 cm, 105,150 ind./m², and 19,274.50 g/m², respectively, while those of the bottom annual panels were 40 cm, 27,300 ind./m², and 17,762.50 g/m², respectively. The dominant fouling organisms with calcified shells mainly included Amphibalanus reticulatus and Pernaviridis. These species had high attachment amounts,could accumulate attachments for a long time, and even might cause secondary blockage, making them the most detrimental to the safety of a cooling system. Moreover,the seasonal upward growth of hydroids and bryozoans can also significantly reduce the efficiency of cooling water intake. We suggest that targeted prevention and control should be carried out according to the larval attachment period of different dominant groups of fouling organisms during June-October, which can greatly improve the prevention and control efficiency. Strengthening the research on the biological cycle phenomenon of the main species and their main environmental impact factors, and establishing a scientific and effective early-warning model are the governance direction of formulating and implementing scientific pollution prevention and control in the future.