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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lawrence Livermore National Security, LLCSite 300: Toxic Emissions Inventory Plan for ABA 2588 California Air Toxics "Hot Spots" Information and Assessment Act of 1987 (Revision 3.0)

The Air Toxics "Hot Spots" Information and Assessment Act (AB 2588 or the “Act”) was enacted in September 1987. Under the Act, stationary sources are required to report the types and quantities of certain toxic substances their facilities routinely release into the air. AB 2588 is designed to provide information to state and local agencies and to the general public on the extent of airborne emissions from stationary sources and the potential public health impacts of those emissions. The San Joaquin Valley Air Pollution Control District (the District) is mandated by the State to implement AB 2588. On March 6, 2015, The State Office of Environmental Health Hazard Assessment (OEHHA) adopted changes to the Air Toxics Hot Spots Program Guidance Manual for the Preparation of Health Risk Assessments. These revisions were designed to incorporate three technical support documents and to provide enhanced protection of children as required under state law (SB 25, Escutia, 1999). Due to these recent changes, and the corresponding potential increases in calculated health risk, the District notified LAWRENCE LIVERMORE NATIONAL SECURITY, LLC that we must be re-evaluated under AB 2588. Pursuant to the Air Toxics "Hot Spots" Information and Assessment Act of 1987, we have prepared a comprehensive, site-specific Toxics Emissions Inventory Plan. The plan specifies in detail how LAWRENCE LIVERMORE NATIONAL SECURITY, LLC will inventory our facility's emissions of all toxic substances on the list of substances subject to the Act. The plan provides a comprehensive and detailed description of the methods that will be used to quantify air releases or potential air releases of listed substances from all points of release. The plan also includes quantification methods which result in accurate and comprehensive characterization of releases and comply with all applicable requirements of the “Hot Spots” regulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Surface modification induced cuprous oxide nanoparticle toxicity to duckweed at sub-toxic metal concentrations

Nanoparticle capping agents are critical for controlling the growth, oxidation state, and final particle size during aqueous synthesis. However, despite the known phytotoxicity of cetyltrimethylammonium bromide (CTAB) to plants, it is used to synthesize metal oxide nanoparticles of uniform size and with mesoporous structure. Among the few studies that have investigated how CTAB influences nanoparticle toxicity, CTAB has never been identified as the primary cause of nanoparticle toxicity in environmental systems; rather nanoparticle surface charge or morphology was identified as the driver of toxicity in environmentally relevant systems. In the current study, CTAB release from CTAB surface modified Cu 2 O nanoparticles (SM-Cu 2 O NPs) inhibited duckweed (Landoltia punctata) growth, even when administered at subtoxic Cu concentrations. Organic ligands, such as humic acid (HA) and ethylenediaminetetraacetic acid (EDTA), lessened growth inhibition associated with exposure to SM-Cu 2 O NPs, likely through electrostatic and hydrophobic interactions with CTAB. Finally, such results highlight the need for a more holistic approach to nanoparticle surface modification and improved communication between toxicologists and synthetic chemists to develop green alternatives for nanoparticle synthesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Lawrence Livermore National Security, LLC Site 300 Facility ID N-472 Toxics Emissions Inventory Plan for AB 2588 California Air Toxics "Hot Spots" Information and Assessment Act of 1987

The Air Toxics "Hot Spots" Information and Assessment Act (AB 2588 or the “Act”) was enacted in September 1987. Under the Act, stationary sources are required to report the types and quantities of certain toxic substances their facilities routinely release into the air. AB 2588 is designed to provide information to state and local agencies and to the general public on the extent of airborne emissions from stationary sources and the potential public health impacts of those emissions. The San Joaquin Valley Air Pollution Control District (the District) is mandated by the State to implement AB 2588.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Pulmonary Toxicity Studies of Lunar Dusts in Rodents

NASA will build an outpost on the lunar surface for long-duration human habitation and research. The surface of the Moon is covered by a layer of fine, reactive dust, and the living quarters in the lunar outpost are expected to be contaminated by lunar dust. NASA established the Lunar Airborne Dust Toxicity Advisory Group (LADTAG) to evaluate the risk of exposure to the dust and to establish safe exposure limits for astronauts working in the lunar habitat. Because the toxicity of lunar dust is not known, LADTAG has recommended investigating its toxicity in the lungs of laboratory animals. After receiving this recommendation, NASA directed the JSC Toxicology Laboratory to determine the pulmonary toxicity of lunar dust in exposed rodents. The rodent pulmonary toxicity studies proposed here are the same as those proposed by the LADTAG. Studies of the pulmonary toxicity of a dust are generally done first in rodents by intratracheal instillation (ITI). This toxicity screening test is then followed by an inhalation study, which requires much more of the test dust and is labor intensive. We succeeded in completing an ITI study on JSC-1 lunar dust simulant in mice (Lam et al., Inhalation Toxicology 14:901-916, 2002, and Inhalation Toxicology 14: 917-928, 2002), and have conducted a pilot ITI study to examine the acute toxicity of an Apollo lunar (highland) dust sample. Preliminary results obtained by examining lung lavage fluid from dust-treated mice show that lunar dust was somewhat toxic (more toxic than TiO2, but less than quartz dust). More extensive studies have been planned to further examine lung lavage fluid for biomarkers of toxicity and lung tissues for histopathological lesions in rodents exposed to aged and activated lunar dust samples. In these studies, reference dusts (TiO2 and quartz) of known toxicities and have industrial exposure limits will be studied in parallel so the relative toxicity of lunar dust can be determined. The ITI results will also be useful for choosing an exposure concentration for the animal inhalation study on a selected lunar dust sample, which is included as a part of this proposal. The animal inhalation exposure will be conducted with lunar dust simulant prior to the study with the lunar dust. The simulant exposure will ensure that the study techniques used with actual lunar dust will be successful. The results of ITI and inhalation studies will reveal the toxicological risk of exposures and are essential for setting exposure limits on lunar dust for astronauts living in the lunar habitat.

Lam, Chiu-wing↗
DOE OSTI2021

CATMoS: Collaborative Acute Toxicity Modeling Suite

Background: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. Objectives: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different endpoints: LD50 value, U.S. Environmental Protection Agency hazard categories, Globally Harmonized System for Classification and Labelling hazard categories, very toxic chemicals (LD50 =50 mg/kg), and non-toxic chemicals (LD50 >2000 mg/kg). Methods: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. Results: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared to in vivo results. Discussion: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for over 800,000 chemicals have been made available via the NTP’s Integrated Chemical Environment. The models are also implemented in a free, standalone open-source tool, OPERA, which allows predictions of new and untested chemicals to be made.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Review of machine learning and deep learning models for toxicity prediction

The ever-increasing number of chemicals has raised public concerns due to their adverse effects on human health and the environment. To protect public health and the environment, it is critical to assess the toxicity of these chemicals. Traditional in vitro and in vivo toxicity assays are complicated, costly, and time-consuming and may face ethical issues. These constraints raise the need for alternative methods for assessing the toxicity of chemicals. Recently, due to the advancement of machine learning algorithms and the increase in computational power, many toxicity prediction models have been developed using various machine learning and deep learning algorithms such as support vector machine, random forest, k-nearest neighbors, ensemble learning, and deep neural network. This review summarizes the machine learning- and deep learning-based toxicity prediction models developed in recent years. Support vector machine and random forest are the most popular machine learning algorithms, and hepatotoxicity, cardiotoxicity, and carcinogenicity are the frequently modeled toxicity endpoints in predictive toxicology. It is known that datasets impact model performance. The quality of datasets used in the development of toxicity prediction models using machine learning and deep learning is vital to the performance of the developed models. The different toxicity assignments for the same chemicals among different datasets of the same type of toxicity have been observed, indicating benchmarking datasets is needed for developing reliable toxicity prediction models using machine learning and deep learning algorithms. This review provides insights into current machine learning models in predictive toxicology, which are expected to promote the development and application of toxicity prediction models in the future.

Research & Experimental Medicine↗
DOE OSTI2022

Machine learning models for rat multigeneration reproductive toxicity prediction

Reproductive toxicity is one of the prominent endpoints in the risk assessment of environmental and industrial chemicals. Due to the complexity of the reproductive system, traditional reproductive toxicity testing in animals, especially guideline multigeneration reproductive toxicity studies, take a long time and are expensive. Therefore, machine learning, as a promising alternative approach, should be considered when evaluating the reproductive toxicity of chemicals. We curated rat multigeneration reproductive toxicity testing data of 275 chemicals from ToxRefDB (Toxicity Reference Database) and developed predictive models using seven machine learning algorithms (decision tree, decision forest, random forest, k-nearest neighbors, support vector machine, linear discriminant analysis, and logistic regression). A consensus model was built based on the seven individual models. An external validation set was curated from the COSMOS database and the literature. The performances of individual and consensus models were evaluated using 500 iterations of 5-fold cross-validations and the external validation data set. The balanced accuracy of the models ranged from 58% to 65% in the 5-fold cross-validations and 45%–61% in the external validations. Prediction confidence analysis was conducted to provide additional information for more appropriate applications of the developed models. The impact of our findings is in increasing confidence in machine learning models. We demonstrate the importance of using consensus models for harnessing the benefits of multiple machine learning models (i.e., using redundant systems to check validity of outcomes). While we continue to build upon the models to better characterize weak toxicants, there is current utility in saving resources by being able to screen out strong reproductive toxicants before investing in vivo testing. The modeling approach (machine learning models) is offered for assessing the rat multigeneration reproductive toxicity of chemicals. Our results suggest that machine learning may be a promising alternative approach to evaluate the potential reproductive toxicity of chemicals.

consensus model↗
DOE OSTI2021

Toxicity of hydraulic fracturing wastewater from black shale natural-gas wells influenced by well maturity and chemical additives

Hydraulic fracturing of deep shale formations generates large volumes of wastewater that must be managed through treatment, reuse, or disposal. Produced wastewater liberates formation-derived radionuclides and contains previously uncharacterized organohalides thought to be generated within the shale well, both posing unknown toxicity to human and ecological health. Here, we assess the toxicity of 42 input media and produced fluid samples collected from four wells in the Utica formation and Marcellus Shale using two distinct endpoint screening assays. Broad spectrum acute toxicity was assessed using a bioluminescence inhibition assay employing the halotolerant bacterium Aliivibrio fischeri, while predictive mammalian cytotoxicity was evaluated using a N-acetylcysteine (NAC) thiol reactivity assay. The acute toxicity and thiol reactivity of early-stage flowback was higher than later produced fluids, with levels diminishing through time as the natural gas wells matured. Acute toxicity of early stage flowback and drilling muds were on par with the positive control, 3,5-dichlorophenol (6.8 mg L -1 ). Differences in both acute toxicity and thiol reactivity between paired natural gas well samples were associated with specific chemical additives. Samples from wells containing a larger diversity and concentration of organic additives resulted in higher acute toxicity, while samples from a well applying a higher composition of ammonium persulfate, a strong oxidizer, showed greater thiol reactivity, predictive of higher mammalian toxicity. Both acute toxicity and thiol reactivity are consistently detected in produced waters, in some cases present up to nine months after hydraulic fracturing. These results support that specific chemical additives, the reactions generated by the additives, or the constituents liberated from the formation by the additives contribute to the toxicity of hydraulic fracturing produced waters and reinforces the need for careful consideration of early produced fluid management.

03 NATURAL GAS↗
NASA NTRS1997

Automated Test Systems for Toxic Vapor Detectors

The NASA Toxic Vapor Detection Laboratory (TVDL) at the Kennedy Space Center (KSC), Florida, has been using Personal Computer based Data Acquisition and Control Systems (PCDAS) for about nine years. These systems control the generation of toxic vapors of known concentrations under controlled conditions of temperature and humidity. The PCDAS also logs the test conditions and the test article responses in data files for analysis by standard spreadsheets or custom programs. The PCDAS was originally developed to perform standardized qualification and acceptance tests in a search for a commercial off-the-shelf (COTS) toxic vapor detector to replace the hydrazine detectors for the Space Shuttle launch pad. It has since become standard test equipment for the TVDL and is indispensable in producing calibration standards for the new hydrazine monitors at the 10 part per billion (ppb) level. The standard TVDL PCDAS can control two toxic vapor generators (TVG's) with three channels each and two flow/temperature/humidity (FIFH) controllers and it can record data from up to six toxic vapor detectors (TVD's) under test and can deliver flows from 5 to 50 liters per minute (L/m) at temperatures from near zero to 50 degrees Celsius (C) using an environmental chamber to maintain the sample temperature. The concentration range for toxic vapors depends on the permeation source installed in the TVG. The PCDAS can provide closed loop control of temperature and humidity to two sample vessels, typically one for zero gas and one for the standard gas. This is required at very low toxic vapor concentrations to minimize the time required to passivate the sample delivery system. Recently, there have been several requests for information about the PCDAS by other laboratories with similar needs, both on and off KSC. The purpose of this paper is to inform the toxic vapor detection community of the current status and planned upgrades to the automated testing of toxic vapor detectors at the Kennedy Space Center.

Mattson, C. B.↗
NASA NTRS1997

Automated Test Systems for Toxic Vapor Detectors

The NASA Toxic Vapor Detection Laboratory (TVDL) at the Kennedy Space Center (KSC), Florida, has been using Personal Computer based Data Acquisition and Control Systems (PCDAS) for about nine years. These systems control the generation of toxic vapors of known concentrations under controlled conditions of temperature and humidity. The PCDAS also logs the test conditions and the test article responses in data files for analysis by standard spreadsheets or custom programs. The PCDAS was originally developed to perform standardized qualification and acceptance tests in a search for a commercial off-the-shelf (COTS) toxic vapor detector to replace the hydrazine detectors for the Space Shuttle launch pad. It has since become standard test equipment for the TVDL and is indispensable in producing calibration standards for the new hydrazine monitors at the 10 part per billion (ppb) level. The standard TVDL PCDAS can control two toxic vapor generators (TVG's) with three channels each and two flow/ temperature / humidity (FTH) controllers and it can record data from up to six toxic vapor detectors (TVD's) under test and can deliver flows from 5 to 50 liters per minute (L/m) at temperatures from near zero to 50 degrees Celsius (C) using an environmental chamber to maintain the sample temperature. The concentration range for toxic vapors depends on the permeation source installed in the TVG. The PCDAS can provide closed loop control of temperature and humidity to two sample vessels, typically one for zero gas and one for the standard gas. This is required at very low toxic vapor concentrations to minimize the time required to passivate the sample delivery system. Recently, there have been several requests for information about the PCDAS by other laboratories with similar needs, both on and off KSC. The purpose of this paper is to inform the toxic vapor detection community of the current status and planned upgrades to the automated testing of toxic vapor detectors at the Kennedy Space Center.

Mattson, C. B.↗
NASA NTRS2009

Toxicity of Lunar Dust in Lungs Assessed by Examining Biomarkers in Exposed Mice

NASA plans to build an outpost on the Moon for prolonged human habitation and research. The lunar surface is covered by a layer of soil, of which the finest portion is highly reactive dust. NASA has invited NIOSH to collaboratively investigate the toxicity of lunar dust. Dust samples of respirable sizes were aerodynamically isolated from two lunar soil samples of different maturities (cosmic exposure ages) collected during the Apollo 16 mission. The lunar dust samples, titanium dioxide, or quartz, suspended in normal saline or in Survanta (a bovine lung surfactant), were given to groups of 5 mice (C-57 male) by intrapharyngeal aspiration at 1, 0.3, or 0.1 mg/mouse. The mice were euthanized 7 or 30 days later, and their lungs were lavaged to assess the toxicity biomarkers in bronchioalveolar lavage fluids. The acellular fractions were assayed for total proteins, lactate dehydrogenase activities, and cytokines; the cellular portions were assessed for total cell counts and cell differentials. Results from the high-dose groups showed that lunar dust, suspended in saline, was more toxic than TiO 2, but less toxic than quartz. Lunar dust particles aggregate and settle out rapidly in water or saline, but not in Survanta. Lunar dust suspended in Survanta manifested greater toxicity than lunar dust in saline. The increase in toxicity presumably was due to that Survanta gave a better particle dispersion in the lungs. The two lunar dust samples showed similar toxicity. The overall results showed that lunar dust is more toxic than TiO 2 but less toxic than quartz.

Lam, C.-W.↗
NASA NTRS2015

Toxicity of Mineral Dusts and a Proposed Mechanism for the Pathogenesis of Particle-Induced Lung Diseases

Humans will set foot on the moon again. The lunar surface has been bombarded for 4 billion years by micrometeoroids and cosmic radiation, creating a layer of fine dust having a potentially reactive particle surface. To investigate the impact of surface reactivity (SR) on the toxicity of particles, and in particular, lunar dust (LD), we ground 2 Apollo 14 LD samples to increase their SR and compare their toxicity with those of unground LD, TiO2 and quartz. Intratracheally instilled at 0, 1, 2.5, or 7.5 mg/rat, all dusts caused dose-dependent increases in pulmonary lesions, and enhancement of biomarkers of toxicity assessed in bronchoalveolar lavage fluids (BALF). The toxicity of LD was greater than that of TiO2 but less than that of quartz. Three LDs differed 14-fold in SR but were equally toxic; quartz had the lowest SR but was most toxic. These results show no correlation between particle SR and toxicity. Often pulmonary toxicity of a dust can be attributed to oxidative stress (OS). We further observed dose-dependent and dustcytotoxicity- dependent increases in neutrophils. The oxidative content per BALF cell was also directly proportional to both the dose and cytotoxicity of the dusts. Because neutrophils are short-lived and release of oxidative contents after they die could initiate and promote a spectrum of lesions, we postulate a general mechanism for the pathogenesis of particle-induced diseases in the lung that involves chiefly neutrophils, the source of persistent endogenous OS. This mechanism explains why one dust (e.g., quartz or nanoparticles) is more toxic than another (e.g., micrometer-sized TiO2), why dust-induced lesions progress with time, and why lung cancer occurs in rats but not in mice and hamsters exposed to the same duration and concentration of dust.

Lam, C.‐W.↗