Search NASA⌕ Search

SEARCH · Search NASA

Results for “Contaminants”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

An Acid-Free, Temperature-Based Cation Contamination Removal Strategy for PEM Water Electrolysis

It is widely understood that the durability and reliability of polymer electrolyte membrane (PEM) water electrolyzers are heavily dependent on feedwater purity, with cation contaminants that originate from incomplete water purification and balance of plant materials significantly harming electrolyzer performance. However, contamination remains a challenge and a common cause of failure at the stack level, indicating the need for strategies to recover the performance of contaminated cells. In this study, we investigate the effects of temperature on the uptake, electrochemical impacts, and removal of contaminant calcium and iron cations. Lower operating temperatures increase the sensitivity of the cell performance to contaminant cations, while also decreasing cation uptake and promoting contaminant removal. Computational charge transfer modelling shows that lower temperature increases the concentration of contaminant at the cathode and facilitates their removal from the cell. By testing single cells under scenarios designed to mimic stack temperature dynamics, we investigate low-temperature operation as an approach to stack-relevant contaminant recovery. Together, these results demonstrate that the low-temperature recovery approach is a promising approach for acid-free contamination recovery for PEM water electrolysis to promote stack reliability and durability.

08 HYDROGEN↗
DOE OSTI2020

Amplicon Sequencing Assessment to Measure Microbial Community Response from Heavy Metal Contaminated Soils in Savannah River site, Tims Branch watershed

Long-term presence of heavy metal contamination in soils is correlated with changes in microbial community structures and can lead to the reduction of indigenous species. Tolerance to soil heavy metal toxicity varies among different microbial communities. It remains unclear whether long term effects caused by metal perturbations are associated with soil microbial community dysregulation in Tims Branch watershed. Research Questions: Does heavy metal contamination in Tims Branch soils decrease microbial species diversity significantly compared to non-contaminated soils? Does the species richness decrease in contaminated samples? between samples? Is diversity in low, mid and high contamination soils significantly different compared to control samples? Hypothesis: The relative abundance and diversity of species are significantly altered in soils which are contaminated with heavy metals in the Tims Branch watershed. Objectives: Use amplicon sequencing technology along with bioinformatics to compare bacterial communities between four sites in Tims Branch watershed. Evaluate the percent relative abundance and diversity across the site. Conclusions: All bacterial communities exposed to different heavy metal concentrations were dominated by four major groups (Proteobacteria, Acidobacteria, Chloroflexi and Verrucomicrobia). The dominant phyla Proteobacteria, Acidobacteria and Chloroflexi accounted for 61 % of the relative abundance. Soil bacterial α-diversity, expressed as observed species richness metric and Shannon's diversity index, was the highest in sample location four (high contamination). The lowest observed was at the control location. Species richness increased when concentrations of heavy metals were localized, inferring that the metals can alter microbial community structure. PERMANOVA analysis between contaminated groups tested significant using the Adonis (F (4,29) =1.9712; p < 0.001). There is a 20 percent variation explained between groups (R2 = 0.214). This analysis proves to be beneficial in detecting microbial communities altered by contaminated soils. Moreover, certain concentrations of heavy metals can alter microbial community structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Analysis of furnace contamination on superconducting radio frequency niobium using secondary-ion mass spectrometry

Detection of surface contamination on niobium materials used in superconducting radio frequency (SRF) applications is difficult due to quantitative sensitivity and near-atomic depth resolution needed. Inspection of samples known to have experienced surface contamination was found to have inconsistent nitride coverage after high-temperature nitrogen gas exposure (“doping”). Here we compare contaminating species found on samples treated in several different vacuum furnaces, both “exposed” directly in the chamber and “protected” by containment shielding from evaporative sources with “furnace caps.” Typically, furnace caps are used to impede contamination from reaching the interior surface of cavities during the high-temperature vacuum bake that immediately precedes exposure to nitrogen gas. Although, to date, little is known about the effectiveness of these caps, SIMS results showed that they were effective in limiting contamination arising from the furnace environment. Inspection of sample surfaces by SEM showed a lack of nitrides present on contaminated specimens. TEM with energy dispersive spectroscopy performed on these samples revealed that a carbon-rich layer now existed, indicating that a relatively high contaminant load prevents the nucleation and growth of surface nitrides, while thus inhibiting interstitial nitrogen uptake. Except in extreme cases, subsequent removal of the top several micrometers of the surface via electropolishing appears to effectively eliminate any strong influence on the subsequent SRF cavity performance. With the absence of furnace cleaning, carbon contamination was found to be nearly 10× higher for protected nitrogen-doped and electropolished samples, with minimal metallic contamination detected for both processes. SIMS analysis was also performed to compare the cleanliness of samples fully prepared by such nitrogen “doping” with those prepared by a related process, involving the dissolution of niobium surface oxide and diffusion of oxygen into the surface. This oxygen doping or alloying process offers attractive advantages.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Machine learning models for estimating contamination across different curbside collection strategies

Contaminated recyclables, which are frequently discarded as waste, pose a significant challenge to the implementation of a circular economy. These contaminated recyclables impede the circulation of resources, resulting in higher processing costs at material recovery facilities (MRFs). Over the past few decades, machine learning (ML) models such as linear regression (LR), support vector machine (SVM), and random forest (RF) have evolved to provide new methods for predicting inbound contamination rates in addition to traditional statistical models. In this study, we applied ML models to predict inbound contamination rates using demographic features from 15 counties in the U.S. with different curbside collection strategies. In general, we found that ML models outperformed linear mixed models. Specifically, SVM models had the highest performance (R 2 = 0.75; mean absolute error (MAE) = 0.06), which may be due to their ability to model nonlinear relationships between features and inbound contamination rates. Further, the key predictor was population, with poverty rate being positively correlated and median age negatively correlated with inbound contamination rates. To improve the management of contamination and enhance the implementation of a circular economy, better models are needed to understand and estimate inbound contamination rates as well as identify critical factors in the present and future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluation of Potential Impacts of Free Chlorine during Washing of Fresh-Cut Leafy Greens on Escherichia coli O157:H7 Cross-Contamination and Risk of Illness

Addition of chlorine-based antimicrobial substances to fresh-cut leafy green wash water is done to minimize microbial cross-contamination during processing. We developed the FDA Leafy Green Risk Assessment Model (FDA-LGRAM) to quantify the impact of free chlorine concentration in wash water during fresh-cut lettuce processing on the extent of water-mediated cross-contamination between shredded lettuce and the associated risk of illness due to exposure to Escherichia coli O157:H7. At different contamination prevalence and levels of E. coli O157:H7 on incoming lettuce heads, the model compared the predicted prevalence of contaminated fresh-cut lettuce packages and the risk of illness per serving between: (1) a scenario where fresh-cut lettuce was packaged without washing; and (2) scenarios involving washing fresh-cut lettuce with different levels of free chlorine (0 ppm, 5 ppm, 10 ppm, 15 ppm, and 20 ppm) prior to packaging. Our results indicate that the free chlorine level in wash water has a substantial impact on the predicted prevalence of contaminated fresh-cut lettuce packages and the risk of illness associated with E. coli O157:H7 in fresh-cut lettuce. Results showed that the required level of free chlorine that can minimize water-mediated cross-contamination and reduce the corresponding risk of illness depended on contamination prevalence and levels of E. coli O157:H7 on incoming lettuce heads. Our model also indicated that the pathogen inactivation rate in wash water via free chlorine was a key model parameter that had a significant impact on the extent of cross-contamination during washing and the predicted associated risk of illness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mixed nitrate and metal contamination influences operational speciation of toxic and essential elements

Environmental contamination constrains microbial communities impacting diversity and total metabolic activity. The former S-3 Ponds contamination site at Oak Ridge Reservation (ORR), TN, has elevated concentrations of nitric acid and multiple metals from decades of processing nuclear material. To determine the nature of the metal contamination in the sediment, a three-step sequential chemical extraction (BCR) was performed on sediment segments from a core located upgradient (EB271, non-contaminated) and one downgradient (EB106, contaminated) of the S-3 Ponds. The resulting exchangeable, reducing, and oxidizing fractions were analyzed for 18 different elements. Comparison of the two cores revealed changes in operational speciation for several elements caused by the contamination. Those present from the S-3 Ponds, including Al, U, Co, Cu, Ni, and Cd, were not only elevated in concentration in the EB106 core but were also operationally more available with increased mobility in the acidic environment. Other elements, including Mg, Ca, P, V, As, and Mo, were less operationally available in EB106 having decreased concentrations in the exchangeable fraction. Here, the bioavailability of essential macro nutrients Mg, Ca, and P from the two types of sediment was determined using three metal-tolerant bacteria previously isolated from ORR. Mg and Ca were available from both sediments for all three strains; however, P was not bioavailable from either sediment for any strain. The decreased operational speciation of P in contaminated ORR sediment may increase the dependence of the microbial community on other pools of P or select for microorganisms with increased P scavenging capabilities. Hence, the microbial community at the former S-3 Ponds contamination site may be constrained not only by increased toxic metal concentrations but also by the availability of essential elements, including P.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Simultaneous immobilization of aqueous co-contaminants using a bismuth layered material

The remediation of co-located contaminants in the vadose zone can be challenging due to accessibility and different responses of different contaminants to remedial actions. At the Hanford Site (WA, USA), multiple contaminants are present in the vadose zone and groundwater, including I, Tc, U, Cr, and NO3. We used a bismuth layered oxide in a series of batch experiments to test aqueous removal of multiple contaminants, including Tc, Cr, and U, as well as potentially competing anions, including NO3 and I. The results demonstrated successful removal of all four contaminants (>98% removal from the aqueous phase after 30 days) when tested individually. When contaminants were combined, a slight decrease in Tc removal occurred (-6%). The addition of sediment decreased the removal for Tc and I, but U and Cr removal was unaffected. Competition with anions released from the sediment likely caused the decreased removal of Tc and I and indicated that bismuth is less selective for these two contaminants. The results of these batch tests demonstrated that the bismuth based oxy-hydroxide material is a promising material for sequestering multiple contaminants in situ.

Lawter, Amanda R.↗
DOE OSTI2023

Bioaccumulation of contaminants in Scarabaeidae and Silphidae beetles at sites polluted by coal combustion residuals and radiocesium

Anthropogenic contamination from coal-fired power plants and nuclear reactors is a pervasive issue impacting ecosystems across the globe. As a result, it is critical that studies continue to assess the accumulation and effects of trace elements and radionuclides in a diversity of biota. In particular, bioindicator species are a powerful tool for risk assessment of chemically contaminated habitats. Using inductively coupled plasma mass spectrometry (ICP-MS) and auto-gamma counting, we analyzed trace element and radiocesium contaminant concentrations in Scarabaeidae and Silphidae beetles (Order: Coleoptera), important taxa in decomposition and nutrient cycling, at contaminated and reference sites on the Savannah River Site, South Carolina, U.S. Our results revealed variability in trace element concentrations between Scarabaeidae and Silphidae beetles at uncontaminated and contaminated sites. Compared to Scarabaeidae, Silphidae had higher levels of chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn). Unexpectedly, concentrations of Cr, Cu, and Ni were higher in both taxa at the uncontaminated sites. Scarabaeidae and Silphidae beetles at the coal combustion waste site consistently had high concentrations of arsenic (As), and Scarabaeidae had high concentrations of selenium (Se). Of the 50 beetles analyzed for radiocesium levels, two had elevated radioactivity concentrations, both of which were from a site contaminated with radionuclides. Furthermore, our results suggest carrion beetles may be particularly sensitive to bioaccumulation of contaminants due to their trophic position and role in decomposition, and thus are useful sentinels of trace element and radionuclide contamination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fitness factors impacting survival of a subsurface bacterium in contaminated groundwater

Many factors contribute to the ability of a microbial species to persist when encountering complexly contaminated environments, including time of exposure, the nature and concentration of contaminants, availability of nutritional resources, and possession of a combination of appropriate molecular mechanisms needed for survival. Herein we sought to identify genes that are most important for survival of Gram-negative Enterobacteriaceae in contaminated groundwater environments containing high concentrations of nitrate and metals using the metal-tolerant Oak Ridge Reservation isolate, Pantoea sp. MT58 (MT58). Survival fitness experiments in which a randomly barcoded transposon insertion (RB-TnSeq) library of MT58 was exposed directly to contaminated Oak Ridge Reservation groundwater samples from across a nitrate and mixed metal contamination plume were used to identify genes important for survival with increasing exposure times and concentrations of contaminants, and availability of a carbon source. Genes involved in controlling and using carbon, encoding transcriptional regulators, and related to Gram-negative outer membrane processes were among those found to be important for survival in contaminated Oak Ridge Reservation groundwater. A comparative genomics analysis of 75 Pantoea genus strains allowed us to further separate the survival determinants into core and non-core genes in the Pantoea pangenome, revealing insights into the survival of subsurface microorganisms during contaminant plume intrusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Radiation Monitoring for Volatilized Zinc Contamination Using Gamma-Ray Imaging and Spectroscopy

Gamma-ray imaging is a tool that has grown in importance in the applications of non-destructive assay (NDA) for radioactive survey and analysis of nuclear facilities. Imaging techniques have shown great promise in providing valuable information involving radioactive waste management and contamination prevention. For the application studied in this work, 65 Zn has been identified as a radioactive contaminant during tritium extraction. Due to the volatile nature of 65 Zn under the pressure and temperature changes during extraction operations, 65 Zn can easily travel through components of the extraction system as vapor, making it difficult to trap. Previous research involving the development of a filtration system showed that the 65 Zn can be trapped, mitigating product contamination. However, during the extraction process, direct analysis of the equipment to confirm that zinc contamination is trapped in the filter and has not spread to other components is impractical. Here, in this situation, the need to assay the location of the contamination with little-to-no interference with operations is vital. In this work, we demonstrate the use of a commercialized 3D position-sensitive CdZnTe (CZT) gamma-ray imaging spectrometer to provide analysis of the 65 Zn contamination. Onsite measurements during an extraction process are studied to assess the location and migration of the 65 Zn. The results obtained from real-time glovebox monitoring demonstrate the feasibility of gamma-ray imaging for localizing the contamination and providing a preliminary qualitative assessment that is intended to be used in future work quantifying the contamination build-up and activity over time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Application of electron beam technology to decompose persistent emerging drinking water contaminants: poly- and perfluoroalkyl substances (PFAS) and 1,4-Dioxane

Poly- and perfluoroalkyl substances (PFAS) and 1,4-dioxane are persistent emerging contaminants that are currently under consideration for federal and state-specific regulations in drinking water. Both PFAS and 1,4-dioxane are highly resistant to degradation and are not effectively removed by conventional drinking water treatment systems. Results from the Unregulated Contaminant Monitoring Rule 3 survey showed that >540 sites across the nation are contaminated with both PFAS and 1,4-dioxane. Hence, there is a need to identify technologies that can effectively remove both these contaminants. Water treatment via electron beam (e-beam) has been proven effective at treating a wide range of contaminants, including perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), polychlorinated biphenyls, and trichloroethylene. While the e-beam process is often considered similar to advanced oxidation processes (AOPs), e-beam technology is unique in that it produces both highly oxidizing and reducing species at the same time. The specific objectives of this study were to: (i) determine the effectiveness of 9 MeV electrons provided by the Fermilab’s Accelerator Application Development and Demonstration (A2D2) tool to decompose PFAS and 1,4-dioxane; (ii) assess the formation of byproducts during water treatment; (iii) apply the optimized treatment to field groundwater samples contaminated with PFAS and 1,4-dioxane, and (iv) assess the energy demands for the treatment of these contaminants using e-beam. Results from this study showed that e-beam is effective in treating both 1,4-dioxane and PFAS. Complete degradation of 1,4-dioxane was observed at a dose of 5 kGy for an initial concentration of up to 1 ppm without the need for any sample modification. The electrical energy per order (EEo) for treatment of 1,4-dioxane ranged from 0.46 to 0.72 kWh/m 3 /order and was comparable and even lower, in some cases, than other AOP technologies. Alkaline conditions (pH 13) and low dissolved oxygen concentration (2 mg/L) highly favored the treatment of PFAS by e-beam. Greater than 90% removal of PFOA and PFOS from an initial concentration of 100 to 500 ppb was achieved at a dose of 250 kGy and 500 kGy, respectively, under optimized conditions. The degradation efficiency was not significantly changed when treating other PFAS of fluorinated carbon chain length of 5 to 7 individually at 250 kGy with a removal ranging from 85¬–99% for different compounds. Short chain PFAS (perfluorobutanoate: PFBA and perfluorobutane sulfonate: PFBS) did not degrade under the same conditions at 250 kGy, but 70 to 99% degradation was observed at a higher dose of 1000 kGy. Short chain PFAS (perfluorohexanoate: PFHxA (C5) and perfluoroheptanoate: PFHpA (C6)) were detected after treatment of PFOA, but not after PFOS treatment. Inability to close the mass balance through targeted analysis suggests the presence of other intermediates not detectable by available analytical methods. When treating PFAS mixture containing ten compounds at equimolar concentration of 0.05 µM each, preferential degradation of polyfluorinated compound (6:2 fluorotelomer sulfonate or 6:2 FTS) followed by C8 and C7 compounds was observed as a function of increasing e-beam dose. About 30% degradation of ΣPFAS was observed at 250 kGy and no further removal was observed up to a dose of 1000 kGy. C4 to C6 PFASs showed no degradation, while C3 PFAS (PFBS) showed an increase in concentration by 34% at 1000 kGy due to formation from the breakdown of other long chain PFAS. These results suggested that (a) the reaction kinetics is likely different for different PFAS based on chain length, functional group, and the degree of fluorination of the carbon chain, and (b) there may be intermediates generated from the degradation of 6:2 FTS and C7/C8 compounds that can potentially scavenge hydrated electrons needed for reaction with the untreated PFAS molecules. Treatment of three PFAS-contaminated groundwater samples from two US states showed similar trends as observed in the treatment of equimolar PFAS mixtures. Up to 71% removal of ΣPFAS was achieved in real groundwater samples at 750 kGy and data trend suggested that higher degradation is feasible if higher doses (>1MGy) are applied to treat field samples to overcome matrix effects and competing species. Calculated EEo for PFAS ranged from as low as ~48 to 1081 kWh/m 3 /order depending on the type of PFAS treated. These values are comparable and even lower, in some cases, than other destructive technologies employed for PFAS treatment such as ultrasound, plasma, and photochemical treatment. The results from this study indicate e-beam is a promising approach under favorable conditions and should be explored further as an end-of-train treatment option for PFAS destruction.

1,4-Dioxane↗
DOE OSTI2025

Review of Grey Box/Black Box Data Contamination Metrics on Open and Commercial Models

Dataset contamination is a problem where benchmarks and tasks used to evaluate the capabilities of Large Language Models (LLMs) have been incorporated into the training dataset of the models. This gives a false sense of performance that can overestimate how these models will function on truly unseen data. This problem becomes worse with commercial LLMs with larger and non-accessible training data, so techniques have been developed to try to measure the degree to which a model is contaminated with a benchmark’s data. To understand the effectiveness of these techniques, particularly when evaluating contamination on coding tasks, we review trends and categorize techniques by the degree of access to the model that is required. The research literature on this topic has reported mixed effectiveness of these techniques, so we select a set of black box (text access only) and grey box (access to model loss/probabilities required) techniques and apply them to both commercial and non-commercial models. We implement these metrics as part of a framework to test the contamination of Python code in LLMs to see to what extent we can replicate the effectiveness (or ineffectiveness) of these contamination detection techniques. Though we find mixed results in the capabilities of these metrics to identify contamination, we do observe evidence that they can identify contamination (broadly) in fine-tuned models when both a baseline and fine-tuned model is present. Additionally, similarity metrics were able to identify between contaminated and uncontaminated data even in situations where the data is distributionally similar (e.g., drawn from the same set of code projects).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Angular Correlation Function Estimators Accounting for Contamination from Probabilistic Distance Measurements

With the advent of surveys containing millions to billions of galaxies, it is imperative to develop analysis techniques that utilize the available statistical power. In galaxy clustering, even small sample contamination arising from distance uncertainties can lead to large artifacts, which the standard estimator for two-point correlation functions does not account for. We first introduce a formalism, termed decontamination, that corrects for sample contamination by utilizing the observed cross-correlations in the contaminated samples; this corrects any correlation function estimator for contamination. Using this formalism, we present a new estimator that uses the standard estimator to measure correlation functions in the contaminated samples but then corrects for contamination. We also introduce a weighted estimator that assigns each galaxy a weight in each redshift bin based on its probability of being in that bin. We demonstrate that these estimators effectively recover the true correlation functions and their covariance matrices. Our estimators can correct for sample contamination caused by misclassification between object types as well as photometric redshifts; they should be particularly helpful for studies of galaxy evolution and baryonic acoustic oscillations, where forward modeling the clustering signal using the contaminated redshift distribution is undesirable.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Development of the Contamination Distribution Centered Toxics Mobility Vulnerability Index in the Beaumont–Port Arthur Region of Texas

This study advances the Toxics Mobility Inventory (TMI) and the Toxics Mobility Vulnerability Index (TMVI) to develop a new tool to assess the movement of hazardous substances and their implications for vulnerable communities. It emphasizes the need to include contamination distribution variables in such indices to address disproportionate impacts and more accurately reflect vulnerability. The study uses the TMI framework and TMVI methodology in the Beaumont–Port Arthur region of Texas, also integrating contamination distribution considerations into the analysis to develop a new framework and process. The new Contamination Distribution Centered Toxics Mobility Vulnerability Index (CDC-TMVI) consolidates climate change and topography variables into a broader built environment vulnerability category while introducing a contamination sources category. Using ArcGIS Pro and ToxPi tools, the study evaluates 27 geospatial variables across four categories: built environment vulnerability, social vulnerability, health outcomes, and contamination sources. The results indicate significant contributions from contamination and social vulnerability variables, highlighting areas with higher risks of flooding and air pollution. This article advocates for future research and policy efforts to enhance the integration of contamination sources and their spatial distributions into toxics mobility assessments to better protect vulnerable populations. Furthermore, the unique methodology and findings serve as a basis for developing targeted measures and strategic planning to improve environmental health.

contamination↗
DOE OSTI2021

Assessment of the Impact of the Single Stream Recycling on Paper Contamination in Recovery Facilities and Paper Mills

Contaminated recyclables pose one of the largest roadblocks to an effective implementation of a circular economy system. Current knowledge surrounding the effects of various recycling methods on contamination rates is limited, thus preventing effective quantification of contamination effects. This study aims to fill this knowledge gap by assessing the impact of single stream recycling on paper contamination in MRFs and their end-products based on different composition studies conducted by facilities nationwide. This project expects to provide the foundational knowledge that could catalyze significant cost savings and energy consumption at MRFs and paper mills by understanding the levels of inbound and outbound contamination rates in SSR systems. Statistical analysis conducted in this project utilizes the available nationwide inbound and outbound samples collected as part of material composition and audit studies to identify and measure the significance of various factors on the resultant contamination levels. The research results provide benefits to both the recycling industry and its customers by addressing the causes and impact of contamination in recycled products, particularly with the wide applicability of single stream recycling within the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Contaminant Source Identification from Finite Sensor Data: Perron–Frobenius Operator and Bayesian Inference

Sensors in the built environment ensure safety and comfort by tracking contaminants in the occupied space. In the event of contaminant release, it is important to use the limited sensor data to rapidly and accurately identify the release location of the contaminant. Identification of the release location will enable subsequent remediation as well as evacuation decision-making. In previous work, we used an operator theoretic approach—based on the Perron–Frobenius (PF) operator—to estimate the contaminant concentration distribution in the domain given a finite amount of streaming sensor data. In the current work, the approach is extended to identify the most probable contaminant release location. The release location identification is framed as a Bayesian inference problem. The Bayesian inference approach requires considering multiple release location scenarios, which is done efficiently using the discrete PF operator. The discrete PF operator provides a fast, effective and accurate model for contaminant transport modeling. The utility of our PF-based Bayesian inference methodology is illustrated using single-point release scenarios in both two and three-dimensional cases. The method provides a fast, accurate, and efficient framework for real-time identification of contaminant source location.

42 ENGINEERING↗
DOE OSTI2020

Updates to a Preliminary Probabilistic Performance Assessment Model for Radiological and Chemical Contamination at the West Valley Site, New York - 20420

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351-ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States at the WNYNSC. NFS built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg (640 metric tons) of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations halted in 1972 and never restarted, leaving behind radioactive and chemical wastes. The U.S. Department of Energy (DOE) was required to complete certain waste management activities under the West Valley Demonstration Project (WVDP) Act of 1980 including decommissioning of WVDP facilities. As collaborating agencies, NYSERDA and the DOE are tasked with making decisions about decommissioning and risk reduction for the West Valley Site. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) model to assist the agencies in their decision making process for decommissioning the WVDP and WNYNSC. One important tool that is needed in order to inform the decision-making process is a science-based model of the West Valley Site that evaluates potential future consequences for human health and the environment. This forms the core of the spatial domain of the West Valley PPA Model. The PPA Model, developed using the GoldSim system modeling software, is a tool intended to provide support for decision making that evaluates uncertainty, in a manner that is transparent, defensible, and robust. The PPA Model includes contaminant transport and health effects components, and is organized around geographically-grouped contaminated facilities. These include the waste disposal areas licensed by the U.S. Nuclear Regulatory Commission and the State of New York, a waste tank farm for storage of high level radioactive waste resulting from reprocessing operations, and several areas contaminated with radioactive and chemical constituents. The PPA Model evaluates contaminant transport from these sources to points of exposure across the site and into receiving surface waters and sediments. Hypothetical people and wildlife could be exposed to contamination at these locations, and the effects of these exposures are evaluated. Contaminant transport processes to be evaluated in the PPA Model include groundwater and surface water transport, contaminant translocation by plants and animals, diffusion, and erosion. The evaluation of exposures to people in this preliminary model is limited to a resident farmer scenario, and ecological assessment is performed at the level of a screening analysis. The results of these preliminary evaluations inform future model developments. PPA Model results are subjected to sensitivity analysis in order to determine those pathways and parameters that are most significant in influencing the results. This information allows analysts and decision makers to focus on those aspects of Site behavior and processes. With this information, the decision makers can drive informed, defensible decisions regarding decommissioning of the Site. This paper includes an update of the information presented at WM2019 [1]. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Impacts on product quality attributes of monoclonal antibodies produced in CHO cell bioreactor cultures during intentional mycoplasma contamination events

Abstract A mycoplasma contamination event in a biomanufacturing facility can result in costly cleanups and potential drug shortages. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and penetrate the standard 0.2‐µm filters used in the clarification of harvested cell culture fluid. Previously, we reported a study regarding the ability of Mycoplasma arginini to persist in a single‐use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G 1 (IgG1) antibody. Our previous work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Careful evaluation of certain identified process parameters over time may be used to indicate mycoplasma contamination in CHO cell cultures in a bioreactor before detection from a traditional method. In this report, we studied the changes in the IgG1 product quality produced by CHO cells considered to be induced by the M. arginini contamination events. We observed changes in critical quality attributes correlated with the duration of contamination, including increased acidic charge variants and high mannose species, which were further modeled using principal component analysis to explore the relationships among M. arginini contamination, CHO cell growth and metabolites, and IgG1 product quality attributes. Finally, partial least square models using NIR spectral data were used to establish predictions of high levels (≥10 4 colony‐forming unit [CFU/ml]) of M. arginini contamination, but prediction of levels below 10 4 CFU/ml were not reliable. Contamination of CHO cells with M. arginini resulted in significant reduction of antibody product quality, highlighting the importance of rapid microbiological testing and mycoplasma testing during particularly long upstream bioprocesses to ensure product safety and quality.

60 APPLIED LIFE SCIENCES↗