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Within the energy industry, there are several technologies used to quantify microbiological contamination of fluids and assets. Some of these technologies can also be used to identify or characterize microorganisms of interest. It is important to understand the scope of detection and limitations of individual assays so that accurate, data-driven decisions can be made. Three fluids varying in chemical composition and origin within the energy sector were tested in this study. Serial dilution for detection of acid producing bacteria (APB) and sulfate reducing bacteria (SRB), activity-reaction tests measuring SRB, an assay quantifying bacterial hydrolases, and adenosine triphosphate (ATP) quantification were compared and assessed against molecular microbiological methods (MMM). Data were collected to determine the ease of use, precision, and comparability of the testing technologies to each other. A kill study using organic biocides evaluated the performance of these tests in quantifying changes in the microbiological populations over time. The testing technologies delivered results on the order of minutes (ATP and enzymatic assays) to days (activity-reaction tests and MMM) to weeks (serial dilution). Comparing data from 1stgeneration ATP and the bacterial hydrolase tests to the data generated by the other technologies proved challenging due to the lack of reference standards and equivocal nature of the raw output from those technologies. A relatively high limit of detection was determined for 1st generation ATP technology in fluids where the bioburden was estimated below 104 cells/mL. Interpretation of results in culture-dependent activity-reaction tests was found to be subjective, requiring users to distinguish between visual indicators to estimate bioburden. This was further confounded when testing fluids for industrial uses that have complex mineral content and turbidity. The choice of culture-dependent technology to enumerate SRB resulted in up to 3-log SRB/mL variance compared to other tests. Variable responses of assayed biomolecules to chemical treatment (e.g., biocide) were notable in the kill study, where the choice of testing technology impacted the interpretation of biocide effectiveness. Accurate evaluation of microbiological contamination is essential to operational decision-making in the energy industry. Understanding the strengths and limitations of different testing technologies ensures optimized chemical treatments, reduced costs, and improved environmental outcomes.
Within the energy industry, there are several technologies used to quantify microbiological contamination of fluids and assets. Some of these technologies can also be used to identify or characterize microorganisms of interest. It is important to understand the scope of detection and limitations of individual assays so that accurate, data-driven decisions can be made. Three fluids varying in chemical composition and origin within the energy sector were tested in this study. Serial dilution for detection of acid producing bacteria (APB) and sulfate reducing bacteria (SRB), activity-reaction tests measuring SRB, an assay quantifying bacterial hydrolases, and adenosine triphosphate (ATP) quantification were compared and assessed against molecular microbiological methods (MMM). Data were collected to determine the ease of use, precision, and comparability of the testing technologies to each other. A kill study using organic biocides evaluated the performance of these tests in quantifying changes in the microbiological populations over time. The testing technologies delivered results on the order of minutes (ATP and enzymatic assays) to days (activity-reaction tests and MMM) to weeks (serial dilution). Comparing data from 1stgeneration ATP and the bacterial hydrolase tests to the data generated by the other technologies proved challenging due to the lack of reference standards and equivocal nature of the raw output from those technologies. A relatively high limit of detection was determined for 1st generation ATP technology in fluids where the bioburden was estimated below 104 cells/mL. Interpretation of results in culture-dependent activity-reaction tests was found to be subjective, requiring users to distinguish between visual indicators to estimate bioburden. This was further confounded when testing fluids for industrial uses that have complex mineral content and turbidity. The choice of culture-dependent technology to enumerate SRB resulted in up to 3-log SRB/mL variance compared to other tests. Variable responses of assayed biomolecules to chemical treatment (e.g., biocide) were notable in the kill study, where the choice of testing technology impacted the interpretation of biocide effectiveness. Accurate evaluation of microbiological contamination is essential to operational decision-making in the energy industry. Understanding the strengths and limitations of different testing technologies ensures optimized chemical treatments, reduced costs, and improved environmental outcomes.
As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as “characteristic communities of microorganisms” found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.
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