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At least 487 records · Page 27

The Q 10 of in situ microbial soil respiration varies with mean annual temperature, precipitation, pH, and plant cover: a meta-analysis and spatial prediction of Q 10

The temperature sensitivity of soil microbial respiration, commonly quantified using the Q 10 coefficient, is a key parameter in carbon cycle models. Uncovering how environmental factors affect in situ Q 10 values can therefore provide critical insight into potential shifts in global carbon stocks under climate change. We collected data from previously published field experiments that measured soil microbial respiration across a range of temperatures. We hypothesized that the Q 10 coefficient of in situ soil microbial respiration would vary based on environmental factors including mean annual temperature (MAT), mean annual precipitation (MAP), plant cover type, pH, soil C:N, and latitude. Linear regression revealed that Q 10 correlates negatively with MAT and MAP and positively with pH and absolute latitude. Additionally, average Q 10 varied significantly across different plant cover types; it was highest in mountain grasslands and lowest in tropical moist forests. Variation in microbial Q 10 across environmental factors may arise from underlying mechanisms such as enzyme kinetics, substrate availability and complexity, and microbial adaptation. To capture patterns in Q 10 more comprehensively, we developed a multiple linear regression model of Q 10 based on the most individually significant environmental drivers and applied it to public datasets to generate a global map of predicted Q 10 . Q 10 was higher in high-latitude and high-altitude regions, where large permafrost carbon stores are vulnerable to thawing and decomposition. We also compared fits between the Q 10 equation and a model produced from macromolecular rate theory (MMRT). We found that the MMRT model had the superior fit and may be better suited to model temperature sensitivity of complex biological reactions. Overall, our results emphasize that relationships between microbial Q 10 and environmental variables should be accounted for in climate models. Incorporating these variations in the Q 10 parameter, rather than using a fixed value, will help predict whether CO 2 emissions will be buffered or exacerbated by soil microbial respiration under climate change.

54 ENVIRONMENTAL SCIENCES↗

STREAM: A technology planning and capacity expansion model for the industrial sector

The Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model—STREAM—is an optimization-based modeling tool and analysis framework to assist with strategic planning and technology investments of the industrial sector. This open-source framework is written in Julia using the JuMP package, which enables users to model future “pathways” for incumbent and future production technologies, costs, fuels and energy carriers, and energy and non-energy environmental impacts from industries as they transform in pursuit of a robust and competitive manufacturing sector. The model starts with an initial stock of industrial production technologies and assets at a facility level and then determines pathways that minimize cost, subject to an array of possible constraints on demand, market shares, environmental flows, and other exogenously specified operational considerations such as capacity utilization rates or regional energy costs. Key features of the framework include flexibility to model a wide range of industries and industrial technologies/processes at varying levels of granularity, ability to perform parametric sensitivity analyses, and ability to visualize model results using visualization objects.

capacity expansion↗

Constraining Bedrock Groundwater Residence Times in a Mountain System with Environmental Tracer Observations and Bayesian Uncertainty Quantification: Modeling and Data Package

Groundwater residence times provide fundamental descriptions of hydrologic dynamics and mixing processes in mountainous watersheds. Yet, few observational datasets that can constrain groundwater residence times over broad timescales are available in high elevation mountain systems. Here we present field observations from May 2021 of dissolved noble gases (He, Ne, Ar, Kr, and Xe), Chloroflourcarbons (CFCs), Sulfurhexaflouride (SF6), and tritium (3H) sampled from the Pumphouse Lower Montane study site (wells PLM1, PLM6, and PLM7) within the East River Watershed, Colorado. The presented noble gas (PLM_noblegas_2021.csv) and environmental tracer (PLM_tracers_2021.csv) observation datasets, along with the associated modeling scripts, aide in quantifying groundwater residence times and recharge conditions in a high elevation mountain system. Furthermore, the modeling scripts quantify groundwater residence time and noble gas recharge condition uncertainties using a novel Markov-chain Monte Carlo approach. All data modeling scripts are written in the Python code.

54 ENVIRONMENTAL SCIENCES↗

Ten questions concerning agent-based modeling of occupant behavior for energy and environmental performance of buildings

We report the complexity of occupant behavior is one of the major contributors to uncertainty in building performance simulation. Agent-based modeling (ABM), a computational simulation technique, has gained attention in the occupant modeling field due to its capability and flexibility to capture the heterogeneity and dynamics of human behavior and the emergent effects. While multiple efforts in the past decade have demonstrated the usefulness of the ABM approach for simulating occupants and their impacts on building performance, several crucial matters in the ABM research still remain unexplored. This paper presents ten questions that highlight the most important issues regarding ABM research and applications for occupant behavior in the context of building performance simulation. The questions and answers aim to provide insights into current and future ABM research, and more importantly to inspire new significant questions from young researchers in the field. This research is part of the IEA EBC Annex 79 project, occupant-centric building design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hanford Composite Analysis Special Studies FY2025 - Groundwater Flow Simulation for use in a Comparison of Simulated Concentrations in the Saturated Zone Estimated by the Plateau-to-River Model Versions 8.3 and 9.1

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1, Radioactive Waste Management, a composite analysis (CA) must be completed for the Central Plateau at the Hanford Site. The CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within the modeling domain. This Environmental Calculation File (ECF) details the application of the Plateau-to-River (P2R) Model (CP-57037, Rev. 3, Model Package Report for the P2R Model: Version 9.1) to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support a special analysis associated with the Hanford Site CA. The simulated flow field will support the simulation of fate and transport of contaminants for comparison to the results obtained as part of the CA to evaluate impact of the updated version of the P2R Model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Antarctic dry valley lakes: Relevance to Mars

The similarity of the early environments of Mars and Earth, and the biological evolution which occurred on early Earth, motivates exobiologists to seriously consider the possiblity of an early Martian biota. Environments are being identified which could contain Martian life and areas which may presently contain evidence of this former life. Sediments which were thought to be deposited in large ice-covered lakes are present on Mars. Such localities were identified within some of the canyons of the Valles Marineris and more recently in the ancient terrain in the Southern Hemisphere. Perennially ice-covered Antarctic lakes are being studied in order to develop quantitative models that relate environmental factors to the nature of the biological community and sediment forming processes. These models will be applied to the Martian paleolakes to establish the scientific rationale for the exobiological study of ancient Martian sediments.

Wharton, R. A., Jr.↗

Accessing, Utilizing and Visualizing NASA Remote Sensing Data for Malaria Modeling and Surveillance

This poster presentation reviews the use of NASA remote sensing data that can be used to extract environmental information for modeling malaria transmission. The authors discuss the remote sensing data from Landsat, Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing One (EO-1), Advanced Land Imager (ALI) and Seasonal to Interannual Earth Science Information Partner (SIESIP) dataset.

Kiang, Richard K.↗

InSitu SEM Investigation of Microstructural Damage Evolution and Strain Relaxation in a Melt Infiltrated SiC/SiC Composite

With CMC components poised to complete flight certification in turbine engines on commercial aircraft within the near future, there are many efforts within the aerospace community to model the mechanical and environmental degradation of CMCs. Direct observations of damage evolution are needed to support these modeling efforts and provide quantitative measures of damage parameters used in the various models. This study was performed to characterize the damage evolution during tensile loading of a melt infiltrated (MI) silicon carbide reinforced silicon carbide (SiC/SiC) composite. A SiC/SiC tensile coupon was loaded to a maximum global stress of 30 ksi in a tensile fixture within an SEM while observations were made at 5 ksi increments. Both traditional image analysis and DIC (digital image correlation) were used to quantify damage evolution. With the DIC analysis, microscale damage was observed at the fiber-matrix interfaces at stresses as low as 5 ksi. First matrix cracking took place between 20 and 25 ksi, accompanied by an observable relaxation in strain near matrix cracks. Matrix crack opening measurements at the maximum load ranged from 200 nm to 1.5 m. Crack opening along the fiber-matrix interface was also characterized as a function of load and angular position relative to the loading axis. This characterization was funded by NASA GRC and was performed to support NASA GRC modeling of SiC/SiC environmental degradation

testing↗

Mapping the Concentration Distribution of Contaminant Plumes to the Computational Grid of the Plateau to River Model (Ver. 8.3)

This environmental calculation file (ECF) outlines the process conducted for defining the initial condition groundwater plumes for select contaminants of interest (COIs) to the Plateau River model version 8.3 (P2Rv8.3) domain (CP-57037, Model Package Report: Plateau to River Groundwater Model Version 8.3). Various data sources were combined into a single set of files defining plume conditions at time 1/1/2018. The resulting files are intended for use as inputs for transport modeling to support forecasts of the Central Plateau contaminant plume fate and transport.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Second-Generation UAM Community Noise Assessment Using the FAA Aviation Environmental Design Tool

Vehicles serving the urban air mobility (UAM) market are anticipated to operate in communities close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration’s Aviation Environmental Design Tool (AEDT), does not support analysis of such operations due to a combined lack of a UAM aircraft performance model and aircraft noise data. This paper discusses second-generation developments to assess the acoustic impact of UAM fleet operations on the community using AEDT and demonstrates its use for representative UAM operations. In particular, methods were developed to add broadband self noise into computed noise-power-distance data, and vertiport-centric operations were evaluated for two concept vehicles.

urban air mobility↗

Critical Load Exceedances for North America and Europe using an Ensemble of Models and an Investigation of Causes for Environmental Impact Estimate Variability: An AQMEII4 Study

Exceedances of critical loads for deposition of sulphur (S) and nitrogen (N) to different ecosystems were estimated using European and North American ensembles of air quality models, under Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4), to identify where risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and Europe 0.125° resolution domains, which were then used to calculate critical load exceedances. New, targeted deposition diagnostics implemented in AQMEII4 allowed an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. New datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2 % to 6.1 %; aquatic ecosystems: 21.2 % to 11.4 %). All models agreed in the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5 % to 75.8 %). The exceedances for herbaceous community richness also decreased between 2010 and 2016, from 13.9 % to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in both predictions of total N deposition and the change in N deposition, and hence in the predicted eutrophication exceedances between the two years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48 % to 4.32 % from 2009 to 2010) while eutrophication exceedance increased slightly (60.2 % to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the two years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulphur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to observed wet deposition of sulphate, nitrate and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases, and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulphate, nitrate and ammonium deposition fluxes between models was linked to the use of updated particle dry deposition parameterizations in some models. However, recent literature and further development of some of the models within the ensemble suggests these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulphur and nitrogen deposition prediction variability was linked to SO 2 and HNO 3 dry deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest and the smallest magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH 3 performance may underestimate the extent of NH 3 emissions fluxes from forested areas. Based on these results, an increased process-research focus is therefore recommended for the following model processes and on observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry deposition, cuticle and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH 3 bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH 3 emissions sources should be included in regional chemical transport models. The choice of land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.

critical loads↗

Habitat model for the Florida Scrub Jay on John F. Kennedy Space Center

The Florida Scrub Jay is endemic to Florida. The John F. Kennedy Space Center (KSC) provides habitat for one of the three largest populations of the Florida Scrub Jay. This threatened bird occupies scrub, slash pine flatwoods, disturbed scrub, and coastal strand on KSC. Densities of Florida Scrub Jays were shown to vary with habitat characteristics but not necessarily with vegetation type. Relationships between Florida Scrub Jay densities and habitat characteristics were used to develop a habitat model to provide a tool to compare alternative sites for new facilities and to quantify environmental impacts. This model is being tested using long term demographic studies of colorbanded Florida Scrub Jays. Optimal habitat predicted by the model has greater than or equal to 50 percent of the shrub canopy comprised of scrub oaks, 20-50 percent open space or scrub oak vegetation within 100 m of a ruderal edge, less than or equal to 15 percent pine canopy cover, a shrub height of 120-170 cm, and is greater than or equal to 100 m from a forest. This document reviews life history, social behavior, food, foraging habitat, cover requirements, characteristics of habitat on KSC, and habitat preferences of the Florida Scrub Jay. Construction of the model and its limitations are discussed.

Breininger, David R.↗

Environmental Exposure Conditions for Teflon FEP on the Hubble Space Telescope Investigated

The Hubble Space Telescope (HST) was launched into low Earth orbit on April 24,1990. During the first servicing mission in December 1993 (3.6 years after launch), multilayer insulation (MLI) blankets were retrieved from the two magnetic sensing systems located on the light shield. Retrieval of one of the solar arrays during this mission also provided MLI blanket material from the solar array drive arm. These MLI materials were analyzed in ground-based facilities, and results indicate that the space-facing outer layer of the MLI, aluminized Teflon FEP (DuPont; fluorinated ethylene propylene), was beginning to degrade. Close inspection of the FEP revealed through-the-thickness cracks in areas with the highest solar exposure and stress concentration. During the second servicing mission in February 1997 (6.8 years after launch), astronauts observed and documented severe cracking in the outer layer of the MLI blankets on both the solar-facing and anti-solar-facing surfaces. During this second mission, some material from the outer layer of the light shield MLI was retrieved and subsequently analyzed in ground-based facilities. After the second servicing mission, a Failure Review Board was convened by NASA Goddard Space Flight Center to address the MLI degradation problem on HST. Members of the Electro-Physics Branch of the NASA Glenn Research Center at Lewis Field participated on this board. To determine possible degradation mechanisms, board researchers needed to consider all environmental constituents to which the FEP MLI surfaces were exposed. On the basis of measurements, models, and predictions, environmental exposure conditions for FEP surfaces on HST were estimated for various time periods from launch in 1990 through 2010, the planned end-of-life for HST. The table summarizes these data including the number and temperature ranges of thermal cycles; equivalent Sun hours; fluence and absorbed radiation dose from solar event x rays; fluence and absorbed dose from solar wind protons and electrons trapped in Earth s magnetic field; fluence of plasma electrons and protons; and atomic oxygen fluence.

Dever, Joyce A.↗

Sensitivity analysis for characterizing the impact of HNGD model on the prediction of hydrogen redistribution in Zircaloy cladding using BISON code

Hydrogen in zirconium cladding is able to precipitate into zirconium hydrides which impacts cladding integrity. The Hydride Nucleation-Growth-Dissolution (HNGD) model in the BISON code accounts for the precipitation and dissolution kinetics of hydride in Zircaloy material. This paper presents global sensitivity analyses of the HNGD model aiming to enhance our understanding of the hydride precipitation phenomena by quantifying the variance that key parameters have on the prediction of hydrogen behavior under various environmental conditions. Here, model predictions are compared to experimental data obtained under two different conditions: 1) with uniformly precharged specimens subjected to a linear thermal gradient, and 2) specimens precharged with a cathodically applied hydride rim at one end of the sample and subjected to an asymmetric thermal gradient. The Sobol sensitivity analysis identifies the key parameters in the HNGD model for both types of specimens. For linear temperature cases, the heat of transport dominates the accuracy of predictions when no precipitation occurs at the cold end, while Terminal Solid Solubility for Dissolution (TSSD) is the most important parameter when precipitation occurs. A large variation in the predicted hydrogen concentration profiles is found in the range of high TSSD due to the occurrence of precipitation. For asymmetric temperature cases, the solubility coefficient gives the largest impact on the predicted hydrogen distribution, as it determines the amount of solute hydrogen dissolved from the initially applied hydride rim. A large discrepancy in hydrogen distribution between simulations and experiments exists with the asymmetric specimens because BISON simulations fail to predict the precipitation of hydride at the cooler end. Comparative studies using former and updated models verifies the significant impact of the hydride growth mechanism on predicted hydrogen concentration profiles. In particular, when hydride initially exists, changes in TSSD generate a large variation in the predicted amount of precipitation by hydride growth, giving large uncertainty in predicting the hydrogen distribution over the sample length. The outputs characterize the significant impact of the hydride growth mechanism in the HNGD model on predicting hydrogen behavior, and improve the understanding of the precipitation of hydride in Zircaloy cladding within a range of expected environmental conditions. The analyses indicate work is still needed to improve the hydride solvus models in the BISON code to accurately predict experimentally observed hydride concentrations and distributions.

36 MATERIALS SCIENCE↗

Old-Aged groundwater contributes to mountain hillslope hydrologic dynamics

Understanding connectivity between the soil and deeper bedrock groundwater is needed to accurately predict a watershed’s response to perturbation, such as drought. Yet, the bedrock groundwater dynamics in mountainous environments are typically under-constrained and excluded from watershed hydrologic models. Here, we investigate the role of groundwater characterized with decadal and longer water ages on the hydrologic and mass-transport processes within a steep snow-dominated mountain hillslope in the Central Rocky Mountains (USA). We quantify subsurface and surface water mass-balance, groundwater flowpaths, and age distributions using the ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models, which are compared to hydrometric and environmental tracer observations. An ensemble of models with varied soil and hydrogeologic parameters reproduces observed groundwater levels and century-scale mean ages inferred from environmental tracers. The numerical models suggest soil water near the toe of the hillslope contains considerable (>60 % of the mass-flux) contributions from bedrock flowpaths characterized with water ages >10 years. Flowpath connectivity between the deeper bedrock and soil systems is present throughout the year, highlighting the potentially critical role of groundwater with old ages on processes such as evapotranspiration and streamflow generation. The coupled numerical model and groundwater age observations show the bedrock groundwater system influences the hillslope hydrodynamics and should be considered in mountain watershed conceptual and numerical models.

54 ENVIRONMENTAL SCIENCES↗

Simulating environmentally-sensitive tree recruitment in vegetation demographic models

Vegetation demographic models (VDMs) endeavor to predict how global forests will respond to climate change. This requires simulating which trees, if any, are able to recruit under changing environmental conditions. We present a new recruitment scheme for VDMs in which functional-type-specific recruitment rates are sensitive to light, soil moisture and the productivity of reproductive trees. We evaluate the scheme by predicting tree recruitment for four tropical tree functional types under varying meteorology and canopy structure at Barro Colorado Island, Panama. We compare predictions to those of a current VDM, quantitative observations and ecological expectations. We find that the scheme improves the magnitude and rank order of recruitment rates among functional types and captures recruitment limitations in response to variable understory light, soil moisture and precipitation regimes. Furthermore, our results indicate that adopting this framework will improve VDM capacity to predict functional-type-specific tree recruitment in response to climate change, thereby improving predictions of future forest distribution, composition and function.

59 BASIC BIOLOGICAL SCIENCES↗

DRDMannTurb: A Python package for scalable, data-driven synthetic turbulence

Synthetic turbulence models (STMs) are used in wind engineering to generate realistic flow fields and are employed as inputs to industrial wind simulations. Examples include prescribing inlet conditions in large eddy simulations that model loads on wind turbines and tall buildings. We are interested in STMs capable of generating fluctuations based on prescribed second-moment statistics since such models can simulate environmental conditions that closely resemble on-site observations. To this end, the widely used Mann model (see Mann, 1994, 1998) is the inspiration for DRDMannTurb. The Mann model is described by three physical parameters: a magnitude parameter influencing the global variance of the wind field and corresponding to the Kolmogorov constant multiplied by the rate of viscous dissipation of the turbulent kinetic energy to the two-thirds, αϵ 2/3 , a turbulence length scale parameter L, and a nondimensional parameter Γ related to the lifetime of the eddies. A number of studies, as well as international standards (e.g., those by the International Electrotechnical Commission (IEC)), include recommended values for these three parameters with the goal of standardizing wind simulations according to observed energy spectra. Yet, having only three parameters, the Mann model faces limitations in accurately representing the diversity of observable spectra. This Python package enables users to extend the Mann model and more accurately fit field measurements through flexible neural network models of the eddy lifetime function. Following Keith et al. (2021), we refer to this class of models as Deep Rapid Distortion (DRD) models. DRDMannTurb also includes a general module implementing an efficient method for synthetic turbulence generation based on a domain decomposition technique. This technique is also described in Keith et al. (2021).

17 WIND ENERGY↗