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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

Initial efforts to develop a deterministic model for predicting and simulating pollen release and downwind concentration to study dependencies of phenology on meteorology will be discussed. The development of a real-time, rapid response pollen release and transport system as a component of the New Mexico Environmental Public Health Tracking System (EPHTS), is based on meteorological models, NASA Earth science results (ESR), and an in-situ network of phenology cameras. The plan is to detect pollen release verified using ground based atmospheric pollen sampling within a few hours using daily MODIS daa in nearly real-time from Direct Broadcast, similar to the MODIS Rapid Response System for fire detection. As MODIS winds down, the NPOESS-VIIRS sensor will assume daily vegetation monitoring tasks. Also, advancements in geostationary satellites will allow 1km vegetation indices at 15-30 minute intervals. The pollen module in EPHTS will be used to: (1) support public health decisions for asthma and allergy alerts in New Mexico, Texas and Oklahoma; (2) augment the Centers for Disease Control and Prevention (CDC)'s Environmental Public Health Tracking Network (EPHTN); and (3) extend surveillance services to local healthcare providers subscribing to the Syndrome Reporting Information System (SYRIS). Previous studies in NASA's public health applications portfolios provide the infrastructure for this effort. The team is confident that NASA and NOAA ESR data, combined into a verified and validated dust model will yield groundbreaking results using the modified dust model to transport pollen. The growing ESR/health infrastructure is based on results from a rapid prototype scoping effort for pollen detection and simulation carried out by the principal investigators.

Luvall, Jeffrey↗
DOE OSTI2024

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

Abstract Background The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network. Results Prediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power. Conclusions Our study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Aghdam, Rosa↗
DOE OSTI2024

Curl up with a good B : detecting ultralight dark matter with differential magnetometry

Ultralight dark matter (such as kinetically mixed dark-photon dark matter or axionlike dark matter) can source an oscillating magnetic-field signal at the Earth’s surface, which can be measured by a synchronized array of ground-based magnetometers. The global signal of ultralight dark matter can be robustly predicted for low masses, when the wavelength of the dark matter is larger than the radius of the Earth, $λ_{DM}$ $\gg$ R. However, at higher masses, environmental effects, such as the Schumann resonances, can become relevant, making the global magnetic-field signal B difficult to reliably model. In this work, we show that ∇ × B is robust to global environmental details, and instead only depends on the local dark matter amplitude. We therefore propose to measure the local curl of the magnetic field at the Earth’s surface, as a means for detecting ultralight dark matter with $λ_{DM}$ ≲ R. As this measurement requires vertical gradients, it can be done near a hill/mountain. Our measurement scheme not only allows for a robust prediction, but also acts as a background rejection scheme for external noise sources. We show that our technique can be the most sensitive terrestrial probe of dark-photon dark matter for frequencies 10 Hz ≤ $f_{A'}$ ≤ 1 kHz (corresponding to masses 4 × 10 –14 eV ≤ $m_{A'}$ ≤ 4 × 10 –12 eV). It can also achieve sensitivities to axionlike dark matter comparable to the CAST helioscope, in the same frequency range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Coupled uptake and conversion of C 12 H 26 and NO on Pd/SSZ-13: Experiments and modeling

The uptake of NO in the presence of C 12 H 26 (dodecane) and H 2 O over a Pd/SSZ-13 washcoated Passive NOx Adsorber (PNA) monolith is reported. When a co-feed containing C 12 H 26 and NO is supplied to an unsaturated (with C 12 H 26 ) sample, the NO uptake is unaffected but during the subsequent temperature ramp the release of trapped NO is delayed from 175°C to over 220°C. The release delay is beneficial for PNA performance as the primary NO x aftertreatment technology, Selective Catalytic Reduction (SCR), is not operated below 200°C. However, pre-saturation of C 12 H 26 followed by the same NO and C 12 H 26 co-feed results in a decrease in the NO uptake compared to the NO-only feed. We conjecture that C 12 H 26 pre-adsorbed on the exterior surface of the sample blocks NO access to the pores, decreasing the number of available sites for NO uptake. Oxidation of C 12 H 26 leads to the generation of partial oxidation product CO at lower temperatures (<250°C) and deep oxidation product CO 2 at higher temperatures. Carbon monoxide binds strongly to Pd sites with NO and can delay NO release. A Pd/SSZ-13 washcoated monolith model developed in an earlier study [Ambast et al., Appl. Catal. B. Environmental (2021)] is upgraded to include C 12 H 26 storage, release, and conversion. Through a systematic combination of judicious experiments, model tuning, and validation, we provide evidence for the underlying NO uptake and release mechanisms in the presence of C 12 H 26 .

42 ENGINEERING↗
NASA NTRS1980

Advanced flight design systems subsystem performance models. Executive summary

Subsystem performance analysis required in flight design to assess the capability of the environmental control and life support system (ECLSS) to support the flight requirements and define operational procedures under contingency flight conditions is described. Current ECLSS modeling techniques are limited in the variety of configurations and they employ batch mode computer programs execution methods. Improvements in the variety of configurations that are modeled and a reduction in effort required for modeling and analysis is accomplished by developing a modular computer program which operates interactively.

Parker, K. C.↗
NASA NTRS2015

The Development of 2700-3000 F Environmental Barrier Coatings for SiC/SiC Ceramic Matrix Composites: Challenges and Opportunities

Environmental barrier coatings (EBCs) and SiCSiC ceramic matrix composites (CMCs) systems will play a crucial role in future turbine engines for hot-section component applications because of their ability to significantly increase engine operating temperatures, reduce engine weight and cooling requirements. The development of prime-reliant environmental barrier coatings is a key to enable the applications of the envisioned 2700-3000F EBC - CMC systems to help achieve next generation engine performance and durability goals. This paper will primarily address the performance requirements and design considerations of environmental barrier coatings for turbine engine applications. The emphasis is placed on current NASA candidate environmental barrier coating systems for SiCSiC CMCs, their performance benefits and design limitations in long-term operation and combustion environments. The efforts have been also directed to developing prime-reliant, self-healing 2700F EBC bond coat; and high stability, lower thermal conductivity, and durable EBC top coats. Major technical barriers in developing environmental barrier coating systems, the coating integrations with next generation CMCs having the improved environmental stability, cyclic durability, erosion-impact resistance, and long-term system performance will be described. The research and development opportunities for turbine engine environmental barrier coating systems by utilizing improved compositions, state-of-the-art processing methods, and simulated environment testing and durability modeling will be discussed.

CMAS Resistance↗
NASA NTRS2004

Human Health Risk Assessment Simulations in a Distributed Environment for Shuttle Launch

During the launch of a rocket under prevailing weather conditions, commanders at Cape Canaveral Air Force station evaluate the possibility of whether wind blown toxic emissions might reach civilian and military personnel in the near by area. In our model, we focused mainly on Hydrogen chloride (HCL), Nitrogen oxides (NOx) and Nitric acid (HNO3), which are non-carcinogenic chemicals as per United States Environmental Protection Agency (USEPA) classification. We have used the hazard quotient model to estimate the number of people at risk. It is based on the number of people with exposure above a reference exposure level that is unlikely to cause adverse health effects. The risk to the exposed population is calculated by multiplying the individual risk and the number in exposed population. The risk values are compared against the acceptable risk values and GO or NO-go situation is decided based on risk values for the Shuttle launch. The entire model is simulated over the web and different scenaria can be generated which allows management to choose an optimum decision.

Thirumalainambi, Rajkumar↗
DOE OSTI2025

Development of chemometric models to classify solid-state U materials by micro-Raman spectroscopy

Discerning uranium (U) particles found in environmental sampling is of interest for monitoring the peaceful use of nuclear material. In this study, a soft independent modeling of class analogy (SIMCA) library was successfully developed for the classification of a four-class system consisting of α-U 3 O 8 , UO 2 , UO 2 (NO 3 ) 2 ·6H 2 O (UNH), and UO 2 O 2 ·4H 2 O (studtite) by Raman spectroscopy in the presence of matrix particulates and additional outliers. Spectral variability between numerous particles of each type revealed appreciable differences as a function of particle size with respect to hydration state and potential oxide phase within each class. Interclass variability was accounted for using both unsupervised and supervised chemometric models. The supervised SIMCA model displayed reasonable sensitivity for each U class and a high degree of specificity by returning whether a spectrum belonged to one class or not. This work demonstrates how Raman spectral features and chemometrics can be used to distinguish U materials from one another and from matrix materials such as flint clay. Combining the outlined chemometric approach with Raman mapping sequences could provide a rapid, nondestructive technique to characterize the chemical composition of a diverse collection of U compounds amid background samples for environmental sampling, nuclear forensics, and industrial applications.

Actinide↗
DOE OSTI2020

A Computationally Efficient Linear Semi-Lagrangian Scheme for the Advection of Microphysical Variables in Cloud-Resolving Models

An efficient semi-Lagrangian (SL) numerical scheme for the advection of positive-definite microphysical variables in cloud-resolving models is proposed. The scheme is a linear combination of SL schemes of the first and second order. The proposed scheme is compared with two high-order, monotonic, nonlinear Eulerian schemes, in two 2D tests. In the first test, advection of a positive scalar field with large gradients is performed within complicated idealized steering flows. In the second test, a hail storm is simulated using the 2D Hebrew University Cloud Model, describing the interactions between 15 size distributions of different microphysical quantities (each distribution is described by 43 mass bins). The proposed scheme is computationally efficient, has a low numerical diffusion and a high level of mass conservation accuracy, and preserves the sum of multiple advected variables as well as the linear relationships between the advected scalar variables. Although the proposed SL scheme is not exactly positive definite, the negative values and their number, which may appear only in the case of very strong gradients, are negligible. The scheme produces results similar to those of nonlinear Eulerian advection schemes while reducing computation time by approximately a factor of 10.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Development of a Genome-Scale Metabolic Model of Clostridium thermocellum and Its Applications for Integration of Multi-Omics Datasets and Computational Strain Design

Solving environmental and social challenges such as climate change requires a shift from our current non-renewable manufacturing model to a sustainable bioeconomy. To lower carbon emissions in the production of fuels and chemicals, plant biomass feedstocks can replace petroleum using microorganisms as biocatalysts. The anaerobic thermophile Clostridium thermocellum is a promising bacterium for bioconversion due to its capability to efficiently degrade lignocellulosic biomass. However, the complex metabolism of C. thermocellum is not fully understood, hindering metabolic engineering to achieve high titers, rates, and yields of targeted molecules. In this study, we developed an updated genome-scale metabolic model of C. thermocellum that accounts for recent metabolic findings, has improved prediction accuracy, and is standard-conformant to ensure easy reproducibility. We illustrated two applications of the developed model. We first formulated a multi-omics integration protocol and used it to understand redox metabolism and potential bottlenecks in biofuel (e.g., ethanol) production in C. thermocellum. Second, we used the metabolic model to design modular cells for efficient production of alcohols and esters with broad applications as flavors, fragrances, solvents, and fuels. The proposed designs not only feature intuitive push-and-pull metabolic engineering strategies, but also present novel manipulations around important central metabolic branch-points. We anticipate the developed genome-scale metabolic model will provide a useful tool for system analysis of C. thermocellum metabolism to fundamentally understand its physiology and guide metabolic engineering strategies to rapidly generate modular production strains for effective biosynthesis of biofuels and biochemicals from lignocellulosic biomass.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Forecast skill of a high-resolution real-time mesoscale model designed for weather support of operations at Kennedy Space Center and Cape Canaveral Air Station

NASA funded Mesoscale Environmental Simulations and Operations (MESO), Inc. to develop a version of the Mesoscale Atmospheric Simulation System (MASS). The model has been modified specifically for short-range forecasting in the vicinity of KSC/CCAS. To accomplish this, the model domain has been limited to increase the number of horizontal grid points (and therefore grid resolution) and the model' s treatment of precipitation, radiation, and surface hydrology physics has been enhanced to predict convection forced by local variations in surface heat, moisture fluxes, and cloud shading. The objective of this paper is to (1) provide an overview of MASS including the real-time initialization and configuration for running the data pre-processor and model, and (2) to summarize the preliminary evaluation of the model's forecasts of temperature, moisture, and wind at selected rawinsonde station locations during February 1994 and July 1994. MASS is a hydrostatic, three-dimensional modeling system which includes schemes to represent planetary boundary layer processes, surface energy and moisture budgets, free atmospheric long and short wave radiation, cloud microphysics, and sub-grid scale moist convection.

Taylor, Gregory E.↗
NASA NTRS2005

Intraspecific differences in bacterial responses to modelled reduced gravity

AIMS: Bacteria are important residents of water systems, including those of space stations which feature specific environmental conditions, such as lowered effects of gravity. The purpose of this study was to compare responses with modelled reduced gravity of space station, water system bacterial isolates with other isolates of the same species. METHODS AND RESULTS: Bacterial isolates, Stenotrophomonas paucimobilis and Acinetobacter radioresistens, originally recovered from the water supply aboard the International Space Station (ISS) were grown in nutrient broth under modelled reduced gravity. Their growth was compared with type strains S. paucimobilis ATCC 10829 and A. radioresistens ATCC 49000. Acinetobacter radioresistens ATCC 49000 and the two ISS isolates showed similar growth profiles under modelled reduced gravity compared with normal gravity, whereas S. paucimobilis ATCC 10829 was negatively affected by modelled reduced gravity. CONCLUSIONS: These results suggest that microgravity might have selected for bacteria that were able to thrive under this unusual condition. These responses, coupled with impacts of other features (such as radiation resistance and ability to persist under very oligotrophic conditions), may contribute to the success of these water system bacteria. SIGNIFICANCE AND IMPACT OF THE STUDY: Water quality is a significant factor in many environments including the ISS. Efforts to remove microbial contaminants are likely to be complicated by the features of these bacteria which allow them to persist under the extreme conditions of the systems.

Non-NASA Center↗
NASA NTRS2012

Assessing the Association Between Asthma and Air Quality in the Presence of Wildfires

Asthma hospital/emergency room (patient) data are used as the foundation for creating a health outcome indicator of human response to environmental air quality. Daily U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) fine particulates (PM2.5) ground data and the U.S. National Aeronautical Space Administration (NASA) MODIS aerosol optical depth (AOD) data were acquired and processed for years of 2007 and 2008. Figure 1 shows the PM2.5 annual mean composite of all the 2007 B-spline daily surfaces. Initial models for predicting the number of weekly asthma cases within a Florida county has focused on environmental variables. Weekly maximums of PM2.5, relative humidity, and the proportions of the county with smoke and fire were the environmental variables included in the model. Cosine and sine functions of time were used to account for seasonality in asthma cases. Counties were considered to be random effects, thereby adjusting for differences in socio ]demographics and other factors. The 2007 predictions for Miami ]Dade county when using B ]splines PM2.5 are displayed in Figures 2.

Young, L. J.↗
DOE OSTI2025

NEPATEC2.0: NEPA Text Corpus v2.0

The National Environmental Policy Act of 1969, as amended (NEPA), is a major environmental law in the United States, requiring Federal agencies to consider and document potential environmental impacts before deciding on a proposed action. Modernization of NEPA and permitting processes faces significant challenges due to the lack of standardized formats and interoperable systems for organizing and sharing NEPA-related information across agencies. Much of the information gathered during NEPA reviews is written into documents such as categorical exclusions, environmental assessments, and environmental impact statements, then filed in predominately independent agency file stores that may or may not be publicly accessible. The application of metadata and data standards, such as those recommended by the Council on Environmental Quality (CEQ), to NEPA documents offers a shared vocabulary and structure for key entities like projects, processes, and documents that can streamline information exchange and enhance collaboration across systems. In this work, we publicly release NEPATEC2.0, an expanded corpus of NEPA documents with associated metadata. NEPATEC2.0 encompasses approximately 120,000 documents from 60,000 projects prepared by more than 60 different agencies. Modeled to align with CEQ metadata standards, NEPATEC2.0 promotes consistency in environmental reviews and supports the ongoing effort to modernize permitting technologies by facilitating more transparent, efficient, and data-driven decision-making. Importantly, NEPATEC2.0 demonstrates the possibilities and limitations of large language model-based prompting to extract information from NEPA documents at scale.

environmental review↗
NASA NTRS2022

Western Montana Ecological Forecasting II: Enhancing Habitat Suitability Modeling of Mustelid Species and Contaminant Monitoring in Northern Montana Using NASA Earth Observations

Environmental contaminants in aquatic ecosystems threaten both human and ecosystem health. Western Montana’s rivers possess great economic and ecological value, yet the status of contaminants in these systems can be unclear. Contaminants such as brominated flame-retardants, heavy metals, and pharmaceuticals negatively affect ecosystem health by traveling through the food chain and bioaccumulating in apex predators. Exposure to these contaminants can result in neurological, endocrine, and reproductive impairments in wildlife and humans. American mink (Neovison vison) and North American river otter (Lontra canadensis) have a predominantly aquatic diet and serve as reliable indicator species of environmental health. Working Dogs for Conservation (WD4C) uses detection dogs to locate scat samples of these species which are assessed for contaminants by the Virginia Institute of Marine Science (VIMS). With Software for Assisted Habitat Modeling (SAHM), the team generated current (2013-2020) and projected (2021-2040) habitat suitability models for mink and otter utilizing NASA Earth observations from Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement Integrated Multi-Satellite Retrievals for GPM (GPM IMERG), Shuttle Radar Topography Mission (SRTM), and Soil Moisture Active Passive (SMAP). The habitat suitability maps’ study region encompassed Flathead National Forest and Blackfeet Indian Reservation. Additionally, the team created site accessibility and precipitation anomaly maps that display the viability of survey locations. The current habitat suitability models performed well (AUC-PR=0.88). The most important predictor variables for suitable habitat were distance to rivers, elevation, and land cover. These end products will further inform WD4C survey site selection and contaminant monitoring.

Chelsea Morton↗
DOE OSTI2022

How do soil microbes shape ecosystem biogeochemistry in the context of global change?

Earth system models disagree on the future of global soil carbon C, with projections ranging from losses of 70 Pg to gains of 250 Pg by the year 2100 (Todd-Brown et al., 2014). This disagreement is due, in part, to the high degree of uncertainty in the mechanisms that control soil C, the largest dynamic pool of organic C on Earth. It remains unclear how climate change, rising atmospheric CO2 levels, and other environmental changes will combine to affect global soil C. As key engineers of biogeochemical cycling, microbes play a crucial role in soil C responses to these environmental changes. Yet, the path toward representing microbes in soil models remains uncertain. Furthermore, we address four burning questions relevant for modelling microbial ecological, evolutionary, and biogeochemical processes in soils: (1) What is the role of soil microbes in biogeochemical cycling? (2) Does microbial community composition matter for soil carbon cycling? (3) Which ecological and evolutionary processes contribute to functional changes? (4) How should we model microbial eco-evolutionary mechanisms in soil C models?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Critical Role Of Conversion Cost And Comparative Advantage In Modeling Agricultural Land Use Change

The difference in land use modeling approaches is an important uncertain factor in evaluating future climate scenarios in global economic models. We compare five widely used land use modeling approaches: constrained optimization, constant elasticity of transformation (CET), the additive form of constant elasticity of transformation (ACET), logit, and Ricardian. We demonstrate that the approaches differ not only by the extent of parameter uses but also by the definition of conversion cost and the consideration of comparative advantage implied by land heterogeneity. We develop a generalized hybrid approach that incorporates ACET/logit and Ricardian to account for both conversion cost and comparative advantage. We use this hybrid approach to estimate future climate impacts on agriculture. We find a welfare loss of about 0.38–0.46% of the global GDP. We demonstrate that ignoring land heterogeneity or land conversion costs underestimates climate impacts on agricultural production and welfare.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Newly Identified Climatically and Environmentally Significant High-Latitude Dust Sources

Dust particles from high latitudes have a potentially large local, regional, and global significance to climate and the environment as short-lived climate forcers, air pollutants, and nutrient sources. Identifying the locations of local dust sources and their emission, transport, and deposition processes is important for understanding the multiple impacts of high-latitude dust (HLD) on the Earth’s systems. Here, we identify, describe, and quantify the source intensity (SI) values, which show the potential of soil surfaces for dust emission scaled to values 0 to 1 concerning globally best productive sources, using the Global Sand and Dust Storms Source Base Map (G-SDS-SBM). This includes 64 HLD sources in our collection for the northern (Alaska, Canada, Denmark, Greenland, Iceland, Svalbard, Sweden, and Russia) and southern (Antarctica and Patagonia) high latitudes. Activity from most of these HLD sources shows seasonal character. It is estimated that high-latitude land areas with higher (SI ≥ 0.5), very high (SI ≥ 0.7), and the highest potential (SI ≥ 0.9) for dust emission cover > 1 670 000 km 2 , > 560 000 km 2 , and > 240 000 km 2 , respectively. In the Arctic HLD region (≥ 60◦ N), land area with SI ≥ 0.5 is 5.5 % (1 035 059 km 2 ), area with SI ≥ 0.7 is 2.3 % (440 804 km 2 ), and area with SI ≥ 0.9 is 1.1 % (208 701 km 2 ). Minimum SI values in the northern HLD region are about 3 orders of magnitude smaller, indicating that the dust sources of this region greatly depend on weather conditions. Our spatial dust source distribution analysis modeling results showed evidence supporting a northern HLD belt, defined as the area north of 50◦ N, with a “transitional HLD-source area” extending at latitudes 50–58◦ N in Eurasia and 50–55◦ N in Canada and a “cold HLD-source area” including areas north of 60◦ N in Eurasia and north of 58◦ N in Canada, with currently “no dust source” area between the HLD and low-latitude dust (LLD) dust belt, except for British Columbia. Using the global atmospheric transport model SILAM, we estimated that 1.0 % of the global dust emission originated from the high-latitude regions. About 57 % of the dust deposition in snow- and ice-covered Arctic regions was from HLD sources. In the southern HLD region, soil surface conditions are favorable for dust emission during the whole year. Climate change can cause a decrease in the duration of snow cover, retreat of glaciers, and an increase in drought, heatwave intensity, and frequency, leading to the increasing frequency of topsoil conditions favorable for dust emission, which increases the probability of dust storms. Our study provides a step forward to improve the representation of HLD in models and to monitor, quantify, and assess the environmental and climate significance of HLD.

high latitude dust↗