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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Matching ecohydrological processes and scales of banded vegetation patterns in semiarid catchments

While the claim that water-carbon interactions result in spatially coherent vegetation patterning is rarely disputed in many arid and semiarid regions, the significance of the detailed water pathways and other high frequency variability remain an open question. How the short temporal scale meteorological fluctuations form the long-term spatial variability of available soil water in complex terrains due to the various hydrological, land surface, and vegetation dynamic feedbacks frames the scope of the work here. Knowledge of the detailed mechanistic feedbacks among soil, plants, and the atmosphere will lead to advances in our understanding of plant water availability in arid and semiarid ecosystems and will provide insights for future model development concerning vegetation pattern formation. In this paper, quantitative estimates of water fluxes and vegetation productivity are provided for a semiarid ecosystem with established vegetation bands on hillslopes using numerical simulations. A state-of-the-science process based ecohydrological model is used, which resolves hydrological and plant physiological processes at the relevant space and time scales, for relatively small periods (e.g., decades) of mature ecosystems (i.e., spatially static vegetation distribution). To unfold the mechanisms that shape the spatial distribution of soil moisture, plant productivity and the relevant surface/subsurface and atmospheric water fluxes, idealized hillslope numerical experiments are constructed, where the effects of soil type, slope steepness, and overland flow accumulation area are quantified. Those mechanisms are also simulated in the presence of complex topography features on landscapes. Finally, the main results are (a) short temporal scale meteorological variability and accurate representation of the scales at which each ecohydrological process operates are crucial for the estimation of the spatial variability of soil water availability to the plant root zone; (b) water fluxes such as evapotranspiration, infiltration, runoff-run-on, and subsurface soil water movement have a dynamic short temporal scale behavior that determines the long-term spatial organization of plant soil water availability in ecosystems with established vegetation patterns; and (c) hypotheses concerning the hydrological responses that can lead to vegetation pattern formation have to accommodate realistic and physically based representations of the fast dynamics of key ecohydrological fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Diagnosing phosphorus limitations in natural terrestrial ecosystems in carbon cycle models

Abstract Most of the Earth System Models ( ESMs ) project increases in net primary productivity ( NPP ) and terrestrial carbon (C) storage during the 21st century. Despite empirical evidence that limited availability of phosphorus (P) may limit the response of NPP to increasing atmospheric CO 2 , none of the ESMs used in the previous Intergovernmental Panel on Climate Change assessment accounted for P limitation. We diagnosed from ESM simulations the amount of P need to support increases in carbon uptake by natural ecosystems using two approaches: the demand derived from (1) changes in C stocks and (2) changes in NPP . The C stock‐based additional P demand was estimated to range between −31 and 193 Tg P and between −89 and 262 Tg P for Representative Concentration Pathway ( RCP ) 2.6 and RCP8.5 , respectively, with negative values indicating a P surplus. The NPP ‐based demand, which takes ecosystem P recycling into account, results in a significantly higher P demand of 648–1606 Tg P for RCP2 .6 and 924–2110 Tg P for RCP8 .5. We found that the P demand is sensitive to the turnover of P in decomposing plant material, explaining the large differences between the NPP ‐based demand and C stock‐based demand. The discrepancy between diagnosed P demand and actual P availability (potential P deficit) depends mainly on the assumptions about availability of the different soil P forms. Overall, future P limitation strongly depends on both soil P availability and P recycling on ecosystem scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Electrochemically recovered struvite matches conventional fertilizers in soil nutrient supply

Phosphorus (P) is an essential macronutrient for agriculture, yet global reliance on finite phosphorite reserves raises concerns about long-term food and nutrient security. Struvite (MgNH 4 PO 4 ·6H 2 O), a mineral recovered from municipal wastewater, represents a sustainable and circular source of P, but uncertainty remains regarding its nutrient availability relative to conventional fertilizers. This study evaluated the fertilizer value and environmental safety of electrochemically recovered struvite (RecoP) in comparison with diammonium phosphate (DAP), triple superphosphate (TSP), and rock phosphate (RockP). Nutrient availability, potential contaminant concentrations, and soil P and nitrogen (N) dynamics were assessed using standardized chemical analyses and an 8-week incubation experiment across three soils with contrasting soil types. RecoP contained 14.7% citrate-soluble P, significantly greater than RockP and comparable to DAP and TSP. Across all soils, RecoP increased both readily available and moderately labile P pools (p < 0.01), matching the performance of conventional fast-release fertilizers. Despite containing approximately half the total of DAP, RecoP stimulated nitrification rates that were 2.2 times greater than the control and exceeded those of TSP, suggesting that fertilizer-derived N bioavailability, rather than total N loading, governed microbial N transformation responses. Concentrations of potentially toxic elements in RecoP were consistently well below US Environmental Protection Agency regulatory limits thresholds. Collectively, these results indicate that RecoP functions as a readily available source of both P and N, comparable to widely used conventional fertilizers, while meeting environmental safety standards. RecoP therefore represents a viable component of sustainable nutrient management strategies that support P recycling and agricultural productivity.

Kharal, Sudarshan [Ohio Univ., Athens, OH (United ↗
DOE OSTI2022

Adoption of biofuels for marine shipping decarbonization: A long‐term price and scalability assessment

Abstract This study assessed the long‐term annual biofuel production capacity potential and price in the United States and shed light on the prospect of biofuel adoption for marine propulsion. A linear programming model was developed to assist the projections and provide insightful analyses. The projected long‐term (2040) maximum annual capacity of biofuels in the United States is 245 million metric tons (Mt) or 65 billion gallons of heavy fuel oil gallon equivalent (HFOGE) when based on the median feedstock availability. Between 2022 (near‐term) and 2040, the potential biofuel capacity increases by over 40%, attributed to increased feedstock availability. At a price range up to $500/t, biodiesel is the main product, and the annual capacity (12 Mt) is limited to feedstock availability constraints. Biodiesel and corn ethanol are the main biofuels at a price range up to $750/t. At a higher price point (above $750/t), the biofuel types and annual capacities increase substantially (218 Mt per year). Biofuels above this price include gasoline‐, jet‐, and diesel‐range blendstocks, as well as bio‐methanol, bio‐propane, and biogas. This study concludes that the US domestic feedstock availability coupled with advanced conversion technologies can produce substantial amounts of biofuels to achieve a critical mass and be impactful as alternative marine fuels. There is also a need to improve the biofuel price for marine shipping adoption. Policies and economic incentives that provide temporary financial support would help facilitate maritime biofuel adoption. © 2022 Alliance for Sustainable Energy, LLC. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2023

A phased workflow to define permit‐ready locations for large volume CO 2 injection and storage

Abstract To‐date, only two UIC Class VI permits have been issued by the US Environmental Protection Agency. We illustrate a four‐phase workflow to first identify regional storage resources and then down‐select sites to yield permit‐ready locations that can accept and store large volumes of CO 2 . Specific permit requirements should guide objectives and define deliverables of respective workflow phases. In the first phase we used available regional data and screened structure and injection zones to locate resources that match CO 2 volumes planned to be captured. Available data were also used to assess presence and depth of usable groundwater, the key resource being protected via permitting. We then used advanced, closed‐form, analytical solutions (EASiTool) to estimate CO 2 injectivity into each hydrologically connected injection compartment. In the second phase we acquired and conditioned additional wireline logs and leased available seismic datasets. We interpreted the depositional systems from wireline well‐log character and mapped sandbody geometry to interpolate injection and confining‐zone distribution. Using available data, we mapped faults and locations of freshwater and overpressure (or other capacity‐limiting geologic parameters) in more detail. In the third phase, we used the augmented geologic data to develop a static model for the selected area, extracted the areas of highest interest, and generated and ran dynamic (flow) models. In a fourth phase, we reduced major uncertainties identified in earlier phases. Our case study indicates that to complete preparation of a permit application requires (1) improved lithologic characterization information (thicknesses and horizontal and vertical connectivity) and (2) better definition of poorly defined local faults. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

58 GEOSCIENCES↗
DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗
DOE OSTI2022

Toward Addressing the Challenge to Predict the Heat Capacities of RDX and HMX Energetic Materials

Availability of heat capacity as function of pressure and temperature is an essential prerequisite for development of a computational multiscale strategy capable to address the evolution of microstructure and energy release in advanced high energy density materials. In the case of 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) systems as two of the most studied energetic materials, there are substantial gaps in experimental data, with available heat capacities values distributed only in a region close to standard ambient conditions. In this study we demonstrate how these major experimental limitations can be addressed in the case of the RDX and HMX systems based on the combined use of classical and quantum mechanical calculations. We show that by considering ideal gas properties evaluated using quantum mechanical methods, and residual properties obtained from molecular simulations using fully flexible atomistic force field models, excellent agreement can be obtained for the predicted heat capacities to the most recent experimental values. An important advantage of the current computational methodology is that it allows evaluation of both constant-volume and constant-pressure heat capacities for a broad interval of temperatures and pressures, which encompasses solid and liquid phases conditions. In the case of the solid α and γ phases of RDX and the β phase of HMX, the predicted results follow closely both the available experimental data at standard ambient conditions and the results obtained using density functional theory calculations at high pressures, a regime where experimental data are not available. A perspective to expand the current methodology is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

As urban areas continue to grow and evolve in a world of increasingenvironmental awareness, the need for detailed information regarding residentialenergy consumption patterns has become increasingly important. Though currentmodeling efforts mark significant progress in the effort to better understand thespatial distribution of energy consumption, the majority of techniques are highlydependent on region-specific data sources and often require building- ordwelling-level details that are not publicly available for many regions in the UnitedStates. Furthermore, many existing methods do not account for errors in input datasources and may not accurately reflect inherent uncertainties in model outputs. Wepropose an alternative and more general hybrid approach to high-resolution residentialelectricity consumption modeling by merging a dasymetric model with acomplementary machine learning algorithm. The method’s flexible data requirementand statistical framework ensure that the model both is applicable to a widerange of regions and considers errors in input data sources.

cities↗
DOE OSTI2018

Environmental Constraints that Limit Methanogenesis

Methanogens are active in many different ecosystems, including habitats with biologically-derived organic matter as substrates such as aquatic sediments, wetlands, agricultural or natural soils subject to inundation, sewage digesters, and the anoxic portions of animal digestive tracts. Methanogens are also present in habitats with geochemically-supplied substrates such as hot springs, hydrothermal vents, volcanically-influenced habitats, and, potentially, the deep crustal subsurface. Methanogens as a group tolerate a broad range of physicochemical conditions, including temperatures from -2 to 122°C, pH values of 3.0 to 10.2, salinities up to halite saturation, and pressures of at least 75 MPa. Globally, variations in methane emissions can be explained to a large degree by variations in temperature and water availability. The distribution and activity of methanogens are constrained by ecological interactions that can be stimulatory or competitive, and by physicochemical factors that act at the biochemical or bioenergetic levels. In addition to the constraints placed on methanogens by physicochemical extremes, methanogen distribution and activity are constrained by the availability of energy and nutrients, the presence of inhibitory molecules (most notably oxygen), and the seawater anion, sulfate, due to competitive ecological interactions. Although methanogen tolerances to individual extremes are documented in culture, and the corresponding biochemical adaptations are understood to varying degrees, the natural environment frequently presents combinations of extreme conditions and energy limitations that may limit methanogen distribution to less than the optimally tolerated range of a single parameter. Little is understood about the compound effects of such extremes, nor the commonalities among them that will ultimately form the basis for predictive models of environmental methanogen population distribution. Future work that targets these questions, through a combination of culture work, “omic” analyses, in situ studies, and conceptual and quantitative models, will be needed to better understand the physiological ecology of methanogens.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.

Cloud computing↗
DOE OSTI2020

Bioenergy Technologies in Long-Run Climate Change Mitigation: Results from the EMF-33 Study

Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

bioenergy↗
DOE OSTI2018

A Thermodynamic Model for ZrO 2 (am) Solubility at 25 °C in the Ca 2+ –Na + –H + –Cl - –OH - –H 2 O System: A Critical Review

Zirconium is an important element in the nuclear fuel cycle. Thermodynamic data and models to reliably predict Zr-OH system behavior in various conditions including high ionic strengths are required and currently are unavailable. Most available experimental data are rather old, obtained using inadequate methodologies, and provide equilibrium constant values that differ by many orders of magnitude. Previous reviews have recommended values based on available data. These reviews used all of the available data, including poor quality data, in a global fit to determine these values. This has resulted in recommended thermodynamic models with a large number of polynuclear species and a number of mononuclear species with values of thermodynamic constants for the solubility product of ZrO 2 (am) and Zr-OH hydrolysis constants that are many orders of magnitude different than those for the reliable analogous Hf reactions. In this critical review, we have evaluated the quality of the available data, selected only those data that are of high quality, and reinterpreted all of the high quality data using SIT and Pitzer models for applications to high ionic strength solutions. Herein for 25°C we 1) present formation constant values for ZrOH 3+ , Zr(OH) 2+ 2 , Zr(OH) 4 (aq), Zr(OH) 5 - , and Zr(OH) 6 2- , and the solubility product for ZrO 2 (am) which are consistent with the Hf system, 2) report a revised value for the formation of Ca 3 Zr(OH) 6 4+ , 3) show that several hypothetical polynuclear species (Zr 3 (OH) 9 3+ , Zr 4 (OH) 15 + , and Zr 4 (OH) 16 (aq)) proposed in previous reviews are not needed, and 4) show that polynuclear species (Zr 3 (OH) 4 8+ and Zr 4 (OH) 8 8+ ) are not important in a very extensive H + concentration range (0.1 to 10 -15.4 mol·kg -1 ). Our review has also resulted in SIT and Pitzer ion-interaction parameters applicable to as high ionic strength solutions as 5.6 mol·kg -1 in NaCl, 2.11 mol·kg -1 in CaCl 2 , and 23.5 mol·kg -1 in NaOH.

solubility, ZrO2(am), solubility product, thermody↗
DOE OSTI2024

Stereo-DIC Challenge 1.0 – Rigid Body Motion of a Complex Shape

Background Stereo-DIC is a widely used optical measurement technique that provides a dense full-field 3D measurement of the shape, displacement, and strain of a solid sample. When compared with 2D-DIC, Stereo-DIC provides greater flexibility and expands its use beyond flat, planar specimens. Furthermore, the widespread availability of commercial systems has led to the adoption of the technique throughout industry, academia, and government research labs. Objective Even though some research has been done to understand the effects of different experimental and stereo-DIC parameters, no reference is available to benchmark and compare the performance of current stereo-DIC algorithms to each other. Methods This paper provides the description and analysis of a carefully controlled 3D experiment and associated images used to compare the results from five subset based DIC software packages. Both the images and analysis codes used in this paper to compare the results are described here and are available for download and use for continued research. Results We show that over a very large range of motion, the 3D errors are very small, less than 80μm over a travel of ±20 mm out-of-plane and ±20 mm in-plane. While all codes performed similarly, there are important differences noted in the paper. Conclusion The image sets and results comparison software are hosted by the International DIC Society (www.iDICs.org) and are freely available for download and analysis for comparison with results in this paper. Furthermore, it is hoped that this set of images can be used for future research in improving stereo-DIC by future authors.

Algorithms comparison↗
DOE OSTI2015

DRACS thermal performance evaluation for FHR

Direct Reactor Auxiliary Cooling System (DRACS) is a passive decay heat removal system proposed for the Fluoride-salt-cooled High-temperature Reactor (FHR) that combines coated particle fuel and a graphite moderator with a liquid fluoride salt as the coolant. The DRACS features three coupled natural circulation/convection loops, relying completely on buoyancy as the driving force. These loops are coupled through two heat exchangers, namely, the DRACS Heat Exchanger and the Natural Draft Heat Exchanger. In addition, a fluidic diode is employed to minimize the parasitic flow into the DRACS primary loop and correspondingly the heat loss to the DRACS during normal operation of the reactor, and to keep the DRACS ready for activation, if needed, during accidents. To help with the design and thermal performance evaluation of the DRACS, a computer code using MATLAB has been developed. This code is based on a one-dimensional formulation and its principle is to solve the energy balance and integral momentum equations. By discretizing the DRACS system in the axial direction, a bulk mean temperature is assumed for each mesh cell. The temperatures of all the cells, as well as the mass flow rates in the DRACS loops, are predicted by solving the governing equations that are obtained by integrating the energy conservation equation over each cell and integrating the momentum conservation equation over each of the DRACS loops. In addition, an intermediate heat transfer loop equipped with a pump has also been modeled in the code. This enables the study of flow reversal phenomenon in the DRACS primary loop, associated with the pump trip process. Experimental data from a High-Temperature DRACS Test Facility (HTDF) are not available yet to benchmark the code. A preliminary code validation is performed by using natural circulation experimental data available in the literature, which are as closely relevant as possible. The code is subsequently applied to the HTDF that is under construction at the Ohio State University.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Elucidation of Fe-N-C electrocatalyst active site functionality via in-situ X-ray absorption and operando determination of oxygen reduction reaction kinetics in a PEFC

In the past decade the notable effort placed on improving intrinsic electrochemical kinetics of platinum group metal (PGM)-free electrocatalysts for the oxygen reduction reaction (ORR) has led to a significant improvement in both performance and understanding of this class of electrocatalysts. However, a limited amount of this development and understanding has been undertaken using operando electrochemical diagnostics at the membrane electrode assembly (MEA) level. In this work, the operando ORR kinetics on an atomically dispersed iron-nitrogen-carbon ((AD)Fe-N-C) PGM-free electrocatalyst have been examined to extract the reaction order and the activation energy of the ORR. The experiments were carefully designed to ensure the stability/predictability of the electrocatalyst during the data collection process and thus validate the relevance of the values obtained for the aforementioned parameters. A kinetic model that considers a potential-dependent availability of active sites (θ) is proposed. Active site availability is shown to be a function of both the change in the oxidation state (nR) and the redox potential at which the metal center transitions from a higher oxidation state to a lower one (). The resulting model fitting parameters for nR and (0.71 and 0.788 V, respectively) obtained from the analysis of operando data correlate well with those from in situ X-ray absorption near edge structure measurements (nR=0.57) and in situ cyclic voltammetry measurements (0.75 V < <0.8 V) in the MEA environment. The resulting model provides an excellent fit of MEA performance across the range of pressures, temperatures, and potentials under which the data were collected.

Activation energy↗
DOE OSTI2018

Temporal dynamics of CO 2 and CH 4 loss potentials in response to rapid hydrological shifts in tidal freshwater wetland soils

Earth System Models predict climate extremes that will impact regional and global hydrology. Aquatic-terrestrial transition zones like wetlands are subjected to the immediate consequence of climate change with shifts in the magnitude and dynamics of hydrologic flow. Such fluctuating hydrology can alter the nature and rate of biogeochemical transformations and significantly impact the carbon balance of the ecosystem. We tested the impacts of fluctuating hydrology and, specifically, the role of antecedent moisture conditions in determining the dominant carbon loss mechanisms in soils sampled from a tidal freshwater wetland system in the lower Columbia River, WA, USA. Our objective was to understand shifts in biogeochemical processes in response to changing soil moisture, based on soil respiration and methane production rates, and to elucidate such responses based on the observed electron acceptor and metabolite profiles under laboratory conditions. Metabolomics and biogeochemical process rates provided evidence that soil redox was the principal factor driving metabolic function. Fluctuating redox conditions altered terminal electron acceptor and donor availability and recovery strengths of their concentrations in soil such that a disproportionate release of carbon dioxide stemmed from alternative anaerobic degradation processes like sulfate and iron reduction compared to carbon loss due to methano genesis. Our results show that extended and short-term saturation created conditions conducive to increasing metabolite availability for anaerobic decomposition processes, with a significant lag in methanogenesis. In contrast,extended drying caused a cellular-level stress response and rapid recycling of alternate electron acceptors.

anaerobic respiration, tidal wetlands, methane pro↗
DOE OSTI2021

Miscellaneous Electric Loads: Characterization and Energy Savings Potential

Over time, miscellaneous electric loads (MELs) are expected to increase both in magnitude and share of residential and commercial building energy consumption. This trend is most apparent in North America, but it is also occurring in Japan and Europe. However, the contribution of MELs to building energy use is not currently well understood, both because the products in this category are transforming rapidly and the definition and classification of MELs is ambiguous. This study estimated the national energy consumption of 36 MELs using best-available data and found them to comprise 12% of delivered electricity to the U.S. residential and commercial building sectors. If 26 of these MELs were replaced with the most energy-efficient product models available on the market, their energy consumption could be halved to 6% of delivered electricity. National energy models will better account for building energy consumption by incorporating the MELs data collected and analyzed for this study, leading to improved policy decisions.

Miscellaneous electric loads, Plug loads, Taxonomy↗
DOE OSTI2015

Investigating the value of fusion energy using the Global Change Assessment Model

The availability of fusion energy could prove valuable in meeting carbon mitigation targets over the course of the century. In this work, we use recent cost estimates for future fusion power plants in order to incorporate fusion into the Global Change Assessment Model (GCAM), a long-term energy and environment model used to study the interaction between technology, climate, and public policy. Results show that fusion's growth will depend on: the chosen carbon mitigation target (if any); the availability of competing carbon-neutral options for the provision of baseload electrical power, in particular nuclear fission as well as carbon capture and storage; the chosen discount rate; the initial year of availability; and the assumed costs of fusion electricity. We quantify the present value of the fusion option while varying the assumptions about these other parameters, and we find that it is, in general for our range of assumptions, significantly larger than the estimated cost of a comprehensive R&D plan to develop fusion energy. The results emphasize the wisdom in hedging against uncertainty in future technology availability by pursuing the development of multiple options that could feasibly play a major role in the latter half of the century.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗