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At least 1,621 records · Page 90

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NASA NTRS2023

Observational Constraints Reduce Model Spread but Not Uncertainty in Global Wetland Methane Emission Estimates

The recent rise in atmospheric methane (CH 4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH 4 source, estimates of global wetland CH 4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH 4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH 4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH 4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH 4 year −1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH 4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Kuang-Yu Chang↗

NASA NTRS1998

NASA's Space Environments and Effects (SEE) Program: The Pursuit of Tomorrow's Space Technology

A hazard to all spacecraft orbiting the earth and exploring the unknown in deep space is the existence of a harsh and ever changing environment with its subsequent effects. Some of these environmental hazards, such as plasma, extreme thermal excursions, meteoroids, and ionizing radiation result from natural sources, whereas others, such as orbital debris and neutral contamination are induced by the presence of spacecraft themselves. The subsequent effects can provide damaging or even disabling effects on spacecraft, its materials, and its instruments. In partnership with industry, academia, and other government agencies, National Aeronautics & Space Administration's (NASA's) Space Environments & Effects (SEE) Program defines the space environments and advocates technology development to accommodate or mitigate these harmful environments on the spacecraft. This program provides a very comprehensive and focused approach to understanding the space environment, to define the best techniques for both flight and ground-based experimentation, to update the models which predict both the environments and the environmental effects on spacecraft, and finally to ensure that this information is properly maintained and inserted into spacecraft design programs. This paper will provide an overview of the Program's purpose, goals, database management and technical activities. In particular, the SEE Program has been very active in developing improved ionizing radiation models and developing related flight experiments which should aid in determining the effect of the radiation environment on modern electronics.

Pearson, Steven D.↗

DOE OSTI2024

Salt marsh soil organic carbon is regulated by drivers of microbial activity

Abstract Soil organic carbon is the foundation for soil health and a livable climate. Organic carbon is concentrated in coastal wetland soils, but dynamics that govern carbon persistence in coastal ecosystems remain incompletely understood. Whether microbial activity results in a gain or loss of carbon depends on environmental conditions that regulate microbial community attributes. We sought to identify which drivers of microbial activity have the greatest impact on organic carbon content in salt marsh soils. To address this question, we used the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) statement to compile data on soil and ecosystem characteristics from 50 studies of over 60 salt marshes located around the world. We conducted a meta-analysis with structural equation modeling, including mediation and moderation analyses, to identify environmental drivers of salt marsh soil organic carbon content. High salinity, pH, nitrogen, and phosphorus were associated with increased microbial biomass carbon and soil organic carbon. Correlations between microbial biomass and organic carbon were strengthened by soil salinity and nitrogen, and weakened by soil water content. These results suggest that environmental conditions that control microbial growth and activity have potential to preserve or degrade organic carbon in salt marsh soils.

Erb, Hailey (ORCID:0000000337295634)↗

NASA NTRS2017

Advantage of Animal Models with Metabolic Flexibility for Space Research Beyond Low Earth Orbit

As the worlds space agencies and commercial entities continue to expand beyond Low Earth Orbit (LEO), novel approaches to carry out biomedical experiments with animals are required to address the challenge of adaptation to space flight and new planetary environments. The extended time and distance of space travel along with reduced involvement of Earth-based mission support increases the cumulative impact of the risks encountered in space. To respond to these challenges, it becomes increasingly important to develop the capability to manage an organisms self-regulatory control system, which would enable survival in extraterrestrial environments. To significantly reduce the risk to animals on future long duration space missions, we propose the use of metabolically flexible animal models as pathfinders, which are capable of tolerating the environmental extremes exhibited in spaceflight, including altered gravity, exposure to space radiation, chemically reactive planetary environments and temperature extremes.In this report we survey several of the pivotal metabolic flexibility studies and discuss the importance of utilizing animal models with metabolic flexibility with particular attention given to the ability to suppress the organism's metabolism in spaceflight experiments beyond LEO. The presented analysis demonstrates the adjuvant benefits of these factors to minimize damage caused by exposure to spaceflight and extreme planetary environments. Examples of microorganisms and animal models with dormancy capabilities suitable for space research are considered in the context of their survivability under hostile or deadly environments outside of Earth. Potential steps toward implementation of metabolic control technology in spaceflight architecture and its benefits for animal experiments and manned space exploration missions are discussed.

metabolic flexibility↗

DOE OSTI2021

Predictive Proxies of Present and Future Lightning in a Superparameterized Model

Abstract A superparameterized climate model is used to assess the global performance of several previously proposed proxies for lightning. In particular, predictors incorporating hydrometeor (ice, graupel) profiles and convective vertical velocities are compared to observations, then used to estimate changes in flash rates with global warming. The choice of microphysics parameterization is also investigated, with all predictors showing higher correlations with Lightning Imaging Sensor/Optical Transient Detector observations when using a 2‐moment scheme compared to a 1‐moment representation. All proxies generally agree in their response to warming over tropical land, with notable decreases in Africa, the Middle East, and northern South America, but disagree over oceans and the midlatitudes. The product of convective available potential energy and precipitation predicts increases over these latter areas, as do the 2‐moment ice‐based proxies, while those of the 1‐moment model tend to show decreases, highlighting the importance of cloud microphysics when using climate models to simulate lightning.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Long-term measurements in a mixed-grass prairie reveal a change in soil organic carbon recalcitrance and its environmental sensitivity under warming

Soil respiration, the major pathway for ecosystem carbon (C) loss, has the potential to enter a positive feedback loop with the atmospheric CO2 due to climate warming. For reliable projections of climate-carbon feedbacks, accurate quantification of soil respiration and identification of mechanisms that control its variability are essential. Process-based models simulate soil respiration as functions of belowground C input, organic matter quality, and sensitivity to environmental conditions. However, evaluation and calibration of process-based models against the long-term in situ measurements are rare. Here, we evaluate the performance of the Terrestrial ECOsystem (TECO) model in simulating total and heterotrophic soil respiration measured during a 16-year warming experiment in a mixed-grass prairie; calibrate model parameters against these and other measurements collected during the experiment; and explore whether the mechanisms of C dynamics have changed over the years. Calibrating model parameters against observations of individual years substantially improved model performance in comparison to pre-calibration simulations, explaining 79–86% of variability in observed soil respiration. Interannual variation of the calibrated model parameters indicated increasing recalcitrance of soil C and changing environmental sensitivity of microbes. Overall, we found that (1) soil organic C became more recalcitrant in intact soil compared to root-free soil; (2) warming offset the effects of increasing C recalcitrance in intact soil and changed microbial sensitivity to moisture conditions. Furthermore, these findings indicate that soil respiration may decrease in the future due to C quality, but this decrease may be offset by warming-induced changes in C cycling mechanisms and their responses to moisture conditions.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2017

Advantage of Animal Models with Metabolic Flexibility for Space Research Beyond Low Earth Orbit

As the world's space agencies and commercial entities continue to expand beyond Low Earth Orbit (LEO), novel approaches to carry out biomedical experiments with animals are required to address the challenge of adaptation to space flight and new planetary environments. The extended time and distance of space travel along with reduced involvement of Earth-based mission support increases the cumulative impact of the risks encountered in space. To respond to these challenges, it becomes increasingly important to develop the capability to manage an organism's self-regulatory control system, which would enable survival in extraterrestrial environments. To significantly reduce the risk to animals on future long duration space missions, we propose the use of metabolically flexible animal models as "pathfinders," which are capable of tolerating the environmental extremes exhibited in spaceflight, including altered gravity, exposure to space radiation, chemically reactive planetary environments and temperature extremes. In this report we survey several of the pivotal metabolic flexibility studies and discuss the importance of utilizing animal models with metabolic flexibility with particular attention given to the ability to suppress the organism's metabolism in spaceflight experiments beyond LEO. The presented analysis demonstrates the adjuvant benefits of these factors to minimize damage caused by exposure to spaceflight and extreme planetary environments. Examples of microorganisms and animal models with dormancy capabilities suitable for space research are considered in the context of their survivability under hostile or deadly environments outside of Earth. Potential steps toward implementation of metabolic control technology in spaceflight architecture and its benefits for animal experiments and manned space exploration missions are discussed.

metabilic flexibility↗

DOE OSTI2024

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Improving North American Wildfire Prediction by Integrating a Machine-Learning Fire Model in a Land Surface Model

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Identifying Key Environmental Factors Explaining Temporal Patterns of DOC Export From Watersheds in the Conterminous United States

The export of dissolved organic carbon (DOC) from a watershed is a key component of the terrestrial biosphere carbon cycle. There is a need to improve our understanding of how and by how much various environmental factors are driving the temporal patterns of DOC export in order to accurately model and evaluate terrestrial carbon storage and fluxes. In this synthesis, we compiled observational data sets from 14 watersheds in the conterminous United States spanning the time period from 1981 to 2017. We used these data sets to examine the relative impacts of various climate, atmospheric deposition, and land cover factors on the temporal patterns of DOC export across watersheds of different sizes and landscape conditions, as well as the time-series autocorrelation of DOC export. Overall, our results suggest that the dominant factor on an annual scale was the amount of precipitation, which had a positive correlation with DOC export from a watershed. Overall increasing nitrogen deposition was coincident with increasing DOC export, and increasing sulfur deposition was coincident with declining DOC export. The seasonal pattern of DOC export was strongly regulated by air temperature, the long-term trend was negatively influenced by increasing sulfur deposition, and no obvious autocorrelation was detected in DOC export. In addition, higher rates of DOC export were positively correlated with greater area of wetlands within a watershed, but was not found to be strongly related to any of the other land cover types.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

Hot gas ingestion characteristics and flow visualization of a vectored thrust STOVL concept

The study presents results obtained at the compressor face of a 9.2-percent scale vectored thrust model in ground effects from Phases I and II of a test program to evaluate the hot ingestion phenomena and control techniques, and to conduct flow visualization of the model flowfield in and out of ground effects, respectively. A description of the model, facility, a new model support system, and a sheet laser illumination system are provided. The findings contain the compressor face pressure and temperature distortions, compressor face temperature rise, and the environmental effects of the hot gas. The environmental effects include the ground plane temperature and pressure distributions, model airframe heating, and the location of the ground flow separation. Results from the sheet laser flow visualization test are also presented.

Johns, Albert L.↗

NASA NTRS2017

Advanced Thermal Barrier and Environmental Barrier Coating Development at NASA GRC

This presentation summarizes NASA's advanced thermal barrier and environmental barrier coating systems, and the coating performance improvements that has recently been achieved and documented in laboratory simulated rig test conditions. One of the emphases has been placed on the toughness and impact resistance enhancements of the low conductivity, defect cluster thermal barrier coating systems. The advances in the next generation environmental barrier coatings for SiCSiC ceramic matrix composites have also been highlighted, particularly in the design of a new series of oxide-silicate composition systems to be integrated with next generation SiC-SiC turbine engine components for 2700F coating applications. Major technical barriers in developing the thermal and environmental barrier coating systems are also described. The performance and model validations in the rig simulated turbine combustion, heat flux, steam and calcium-magnesium-aluminosilicate (CMAS) environments have helped the current progress in improved temperature capability, environmental stability, and long-term fatigue-environment system durability of the advanced thermal and environmental barrier coating systems.

Thermal Barrier and Environmental Barrier Coatings↗

DOE OSTI2024

Environmental monitoring data from the 2022-2023 field experiment at Game Ridge, Missoula County, Montana, USA

This dataset contains sensor data from programmed loggers as well as handheld moisture probes, including weather data, air and soil temperature, and soil volumetric water content. Data files and data dictionary(ies) are uploaded as .csv files. The Users Guide is a .pdf file. Location data can be found in the Google Earth file GameRidge_SitePlotCoordinates.kmz.kml included here. These datasets were collected for Plant Carbohydrate Depletion, Mycorrhizal Networks, and Vulnerability to Drought: An Experimental Test in the Field. This experiment examined the interdependency between plant hydraulics and carbohydrate availability and sought to develop ways to incorporate interactions with below ground symbiotic organisms to better model and quantify forest response to drought. This environmental data was collected to provide context for the fungal community data and Pinus ponderosa physiological data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations

Gross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS- and GPP-related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP-only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2007

Simulation of Malaria Transmission among Households in a Thai Village using Remotely Sensed Parameters

We have used discrete-event simulation to model the malaria transmission in a Thailand village with approximately 700 residents. Specifically, we model the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle under the explicit influences of selected extrinsic and intrinsic factors. Some of the meteorological and environmental parameters used in the simulation are derived from Tropical Rainfall Measuring Mission and the Ikonos satellite data. Parameters used in the simulations reflect the realistic condition of the village, including the locations and sizes of the households, ages and estimated immunity of the residents, presence of farm animals, and locations of larval habitats. Larval habitats include the actual locations where larvae were collected and the probable locations based on satellite data. The output of the simulation includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Simulated transmission under homogeneous environmental condition was compared with that predicted by a SEIR model. Sensitivity of the output with respect to some extrinsic and intrinsic factors was investigated. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. The simulation method is useful for testing transmission hypotheses, estimating the efficacy of insecticide applications, assessing the impacts of nonimmune immigrants, and predicting the effects of socioeconomic, environmental and climatic changes.

Kiang, Richard K.↗

DOE OSTI2025

Estimation Methodology to Evaluate Hypothetical Downwind Impacts from Fusion Plants

The continuing move toward establishing fusion systems for power generation and the associated research to that end is prompting examination of the potential health and safety impacts of such plants to the environment and human health. As many fusion facilities will have tritium inventories on site as part of the fusion fuel, evaluating the potential for downwind impacts from fusion facilities or power plants resulting from accident or routine emissions is a general requirement for assessing location and impacts to workers and the public. As part of siting considerations and permitting, the fusion facilities would be evaluated for potential for downwind concentration and dose impacts. For accident assessment scenarios, the downwind impacts are usually modeled as an instantaneous (or near-instantaneous) release of material transported following the wind. A range of meteorological conditions are usually assessed to determine a bounding case which results in a dose exceeding a specified threshold (e.g., 95 th or 99 th percentile; DOE 2015). This report provides initial estimates of the downwind dose impacts from a potential tritium release at a fusion power plant-relevant facility and identifies potential distances required to limit impacts to nearby population. This effort is meant to provide a bounding analysis and theoretical understanding of impacts of tritium releases for facilities subject to various environmental and atmospheric conditions. Using a Gaussian dispersion model to simulate a brief plume, downwind concentration and dose is projected for tritium oxide. Releases are assumed to consist entirely of tritium oxide due to the increased dose impacts from the oxide form relative to the elemental form of tritium. We also briefly identify how climatological conditions could potentially be used to support risk profile determination.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Impact of Regional Northern Hemisphere Mid-latitude Anthropogenic Sulfur Dioxide Emissions on Local and Remote Tropospheric Oxidants

The unintended consequences of reductions in regional anthropogenic sulfur dioxide (SO2) emissions implemented to protect human health are poorly understood. SO2 decreases began in the 1970s in the US and Europe and are expected to continue into the future, while recent emissions decreases in China are also projected to continue. In addition to the well-documented climate effects (warming) from reducing aerosols, tropospheric oxidation is impacted via aerosol modification of photolysis rates and radical sinks. Impacts on the hydroxyl radical and other trace constituents directly affect climate and air quality metrics such as surface ozone levels. We use the Geophysical Fluid Dynamics Laboratory Atmospheric Model version 3 nudged towards National Centers for Environmental Prediction (NCEP) reanalysis wind velocities to estimate the impact of SO2 emissions from the US, Europe, and China by differencing a control simulation with an otherwise identical simulation in which 2015 anthropogenic SO2 emissions are set to zero over one of the regions. Springtime sulfate aerosol changes occur both locally to the emission region and also throughout the Northern Hemispheric troposphere, including remote oceanic regions and the Arctic. Hydroperoxy (HO2) radicals are directly removed via heterogeneous chemistry on aerosol surfaces, including sulfate, in the model, and we find that sulfate aerosol produced by SO2 emissions from the three individual northern mid-latitude regions strongly reduces both HO2 and hydroxyl (OH) by up to 10 % year-round throughout most of the troposphere north of 30∘ N latitude. Regional SO2 emissions significantly increase nitrogen oxides (NOx) by about 5 %–8 % throughout most of the free troposphere in the Northern Hemisphere by increasing the NOx lifetime as the heterogeneous sink of HO2 on sulfate aerosol declines. Despite the NOx increases, tropospheric ozone decreases at northern mid-latitudes by 1 %–4 % zonally averaged and by up to 5 ppbv in summertime surface air over China, where the decreases in HO2 and OH suppress O3 production. Since 2015 anthropogenic SO2 emissions in China exceed those in the US or Europe, the oxidative response is greatest for the China perturbation simulation. Chemical effects of aerosols on oxidation (reactive uptake) dominate over radiative effects (photolysis rates), the latter of which are only statistically significant locally for the large perturbation over China. We find that the SO2 emissions decrease in China, which has yet to be fully realized, will have the largest impact on oxidants and related species in the Northern Hemisphere free troposphere compared to future decreases in Europe or the US. Our results bolster previous calls for a multipollutant strategy for air pollution mitigation to avoid the unintended consequence of aerosol removal leading to surface ozone increases that offset or mask surface ozone gains achieved by regulation of other pollutants, especially in countries where current usage of high-sulfur emitting fuels may be phased out in the future.

anthropogenic sulfur dioxide emissions↗

NASA NTRS1991

Preliminary ECLSS waste water model

A preliminary waste water model for input to the Space Station Freedom (SSF) Environmental Control and Life Support System (ECLSS) Water Processor (WP) has been generated for design purposes. Data have been compiled from various ECLSS tests and flight sample analyses. A discussion of the characterization of the waste streams comprising the model is presented, along with a discussion of the waste water model and the rationale for the inclusion of contaminants in their respective concentrations. The major objective is to establish a methodology for the development of a waste water model and to present the current state of that model.

Carter, Donald L.↗