Effects of Lead and Arsenic in Soils from Former Orchards on Growth of Three Plant Species.

Historical use of lead arsenate as a pesticide in former orchards of eastern Washington State (USA) has resulted in legacy lead (Pb) and arsenic (As) soil contamination. However, the impacts on plant growth in soils with residual Pb and As contamination have not yet been quantified. To this end, a comparative study of plant growth impacts was performed for native bluegrass (Poa secunda), invasive cheatgrass (Bromus tectorum), and buttercrunch lettuce (Lactuca sativa). Using standard plant growth protocols, germination frequency and biomass growth were measured over a wide range of Pb and arsenate concentrations, with maximum concentrations of 3400 and 790 mg kg-1 for Pb and As, respectively. Results indicated that only the biomass growth for all species decreased in soils with the highest concentrations of Pb and As in the soil, with no impacts on soils with lower residual Pb and arsenate concentrations. No impact on percentage of germination was observed at any soil concentration. These results can be used to determine site-specific soil screening levels for use in ecological risk assessments for Pb and arsenate in soils. Environ Toxicol Chem 2022;41:1459-1465. © 2022 Battelle Memorial Institute. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Fate and transport of unruptured tri-structural isotropic (TRISO) fuel particles in the event of environmental release for advanced and micro reactor applications.

Advanced nuclear reactor designs and advanced fuel types offer safety features that may reduce environmental consequences in an accident scenario when compared to conventional reactors and fuels. One advanced reactor fuel is tri-structural isotropic (TRISO) fuel particles which are approximately 0.9 mm in diameter. TRISO particle mobility, assuming the particle is unruptured and the encapsulated radionuclides are contained, was explored by a theoretical examination of transport through atmosphere, soil and groundwater, surface water, and non-human biota pathways. TRISO particles are too large and dense to travel in the atmosphere except under extreme conditions. TRISO particles are also too large to penetrate most soil profiles and so cannot be transported to or by groundwater. TRISO particles will settle out of the water column in surface waters and thus the transport will depend on the energy of the water body (e.g., waves or floods). TRISO particles could be transported by non-human biota. The size of TRISO particles could allow them to be intentionally ingested by non-human biota as a gastrolith or mimic something typical in an organism's diet. Generally, TRISO particles will have reduced environmental mobility compared to releases of radionuclides in the event of a conventional nuclear reactor accident. The extent of transport has implications in emergency planning zone designations and other considerations for licensing and deploying TRISO-fueled reactors. Further research and experimental work exploring TRISO particle mobility is required to understand the full environmental mobility of TRISO particles in the environment.

Internal Radiation Dose Evaluation for an Unruptured Post Release Tristructural Istropic Fuel Particle for Advanced and Micro-reactor Applications.

ABSTRACT: There are unique benefits from advanced/micro-reactor designs and fuel types that offer safety features in the case of an accident that may reduce environmental consequences compared to conventional reactors and fuels. Tristructural isotropic (TRISO) fuel particles are a robust advanced nuclear fuel type that leads to the unique question of how unruptured, activated TRISO particles will interact with humans. TRISO particles are 900 µm in size, and that particle size restricts internal dose assessment to the ingestion pathway. Activity of the TRISO particle was established by High Temperature Engineering Test Reactor simulations. The TRISO particle encapsulation was assumed to be perfect; exploration of internal dose contribution from radionuclides released from encapsulation was not included. The TRISO particle was assumed to be mixed actively within each alimentary tract compartment such that homogenous distribution could be assumed according to the International Commission on Radiological Protection publication 133. The dose assessment results indicate that the rectosigmoid colon had the highest internal organ dose for both reference male (2.1 Sv) and female (2.3 Sv). The internal dose from ingestion of the scenario-specific TRISO particle was 0.25 Sv for the reference male and 0.29 Sv for the reference female, which exceeds the annual occupational effective dose limit of 0.05 Sv in the Code of Federal Regulations, 10 CFR Part 20 Subpart C. Similarly, the annual occupational limit of 0.5 Sv to any one organ would be exceeded for the left colon, right colon, and rectosigmoid colon for both the reference male and female.

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning.

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 µg UL⁻¹), medium dose (amended at 100 µg UL⁻¹), and high dose (500 µg UL⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.

Modeling long-term risk to environmental and human systems at the Hanford Nuclear Reservation: scope and findings from the initial model.

The Groundwater Protection Project at the US Department of Energy Hanford Site in Washington State is currently developing the means to assess the cumulative impact to human and ecological health and the regional economy and cultures from radioactive and chemical waste that will remain at the Hanford Site after the site closes. This integrated system is known as the System Assessment Capability (SAC). The SAC Risk/Impact Module discussed in the article uses media- and time-specific concentrations of contaminants estimated by the transport models of the integrated system to project potential impacts on the ecology of the Columbia River corridor, the health of persons who might live in or use the corridor or the upland Hanford environment, the local economy, and cultural resources. Preliminary Monte Carlo realizations from the SAC modeling system demonstrate the feasibility of large-scale uncertainty analysis of the complex relationships in the environmental transport of contaminants on the one hand and ecological, human, cultural, and economic risk on the other. Initial impact results show very small long-term risks for the 10 radionuclides and chemicals evaluated. The analysis also helps determine science priorities to reduce uncertainty and suggests what actions matter to reduce risks.