Identification of algal rich microbial blooms in the Sellafield Pile Fuel Storage Pond and the application of ultrasonic treatment to control the formation of blooms

Abstract

The presence of microorganisms in a range of nuclear facilities has been known for many years. In this study the microbial community inhabiting the Pile Fuel Storage Pond (PFSP), which is a legacy open-aired facility on the Sellafield nuclear site, Cumbria, UK, was determined to help target microbial bloom management strategies in this facility. The PFSP is currently undergoing decommissioning and the development of prolonged dense microbial blooms reduces the visibility within the water. Such impairment in the pond water visibility can lead to delays in pond operations, which also has financial implications. Efforts to control the microbial population within the PFSP are ongoing, with the installation of ultrasonic treatment units. Here next generation sequencing techniques focussing on broad targets for both eukaryotic and prokaryotic organisms were used to identify the microbial community. On-site monitoring of photosynthetic pigments indicated when microbial blooms formed and that eukaryotic algae were most likely to be responsible for these events. The sequencing data suggested that the blooms were dominated by members of the class Chrysophyceae, a group of golden algae, while evidence of cyanobacteria and other photosynthetic bacteria was limited, further supporting eukaryotic organisms causing the blooms. The results of sequencing data from 2018 was used to inform a change in the operational settings of the ultrasonic units, while monitoring of the microbial community and photosynthetic pigments trends was extended. Since the changes were made to the ultrasonic treatment, the visibility in the pond was significantly improved, with an absence of a spring bloom in 2020 and an overall reduction in the number of days lost due to microbial blooms annually. This work extends our knowledge of the diversity of microbes able to colonise nuclear fuel storage ponds, and also suggests that sequencing data can help to optimise the performance of ultrasonic treatments, to control algal proliferation in the PFSP facility and other inhospitable engineered systems.