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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA

Abstract. Careful allotment of water resources for irrigation is critical for ensuring the resiliency of agriculture in semiarid regions, and modernizing irrigation technology to minimize inefficient water losses is an important tool for farmers and agricultural economies. While modernizing irrigation technology can achieve reductions in the nonbeneficial use of water, such as bare soil evaporation and nonconsumptive losses, water returned to the landscape is also reduced, often eliminating flow paths that other users rely on. In basins using a combination of surface and groundwater, replenishing aquifer storage by the managed aquifer recharge (MAR) of seasonally available water can mitigate the aquifer drawdown that results from reduced recharge when irrigation efficiency is improved. We examine the effects of MAR on the system-scale efficiency of modernizing irrigation technology and the resulting changes in the reuse of nonconsumptive losses, using a macroscale hydrologic model applied to the semiarid upper Snake River basin (USRB) of western Wyoming and southern Idaho, USA. Irrigation technologies were represented explicitly in the model, and available data informed baseline parameterizations of the irrigation technology. A suite of parameterizations were simulated that updated the existing technologies to be more efficient, both with and without sufficient MAR to cause a stabilization of the aquifer at the present-day head. As expected, simulated changes in irrigation technology resulted in greater downstream export of pristine water and a higher rate of aquifer drawdown when MAR was not simulated. Under current water use and cropping patterns, we were not able to simulate aquifer stabilization and maintain discharge downstream at any level of irrigation efficiency. We found support for the hypothesis that, as efficiency improves, less MAR is required to maintain a stable aquifer than when return flows are reduced due to increased efficiency. To evaluate the hypothesis, we defined the management benefit as a metric that compared the difference between the change in irrigation's net recharge and the change in MAR required as irrigation technology became more efficient. The metric generally indicated that less MAR was needed than net recharge was lost, but only for the most efficient case did the management benefit exceed the MAR needed at the baseline to stabilize the aquifer. Increasing efficiency of irrigation technology reduced the reuse of the gross irrigation derived from prior nonconsumptive losses, but simulating MAR increased reuse for a given parameterization, leading to higher effective irrigation efficiency. We find that local groundwater storage that users depend on is generally more sensitive to management decisions than downstream flows, and the drawdown of the aquifer without MAR always exceeded any decrease in discharge induced by MAR. Improving resource sufficiency in semiarid systems like the USRB will require an array of solutions that will need to balance benefits to local and downstream users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Calcium is associated with specific soil organic carbon decomposition products

Abstract. Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here, we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca–SOC is removed through cation exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, this highlights a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca; in turn, this association can inhibit dissolved organic carbon export or further decomposition. We propose that this mechanism could be driven by Ca hotspots at the microscale shifting local decomposition processes and thereby explaining the co-location of Ca with SOC of a specific composition across different acidic soil environments. Incorporating this biogeochemical process into Earth system models could improve our understanding, predictions, and management of carbon dynamics in soils, as well as accounting for their response to Ca-rich amendments.

Rowley, Mike C. (ORCID:0000000224407855)↗
DOE OSTI2022

A symbolic framework to obtain mid-fidelity models of flexible multibody systems with application to horizontal-axis wind turbines

Abstract. The article presents a symbolic framework (also called computer algebra program) that is used to obtain, in symbolic mathematical form, the linear and nonlinear equations of motion of a mid-fidelity multibody system including rigid and flexible bodies. Our approach is based on Kane's method and a nonlinear shape function representation for flexible bodies. The shape function approach does not represent the state of the art for flexible multibody dynamics but is an effective trade-off to obtain mid-fidelity models with few degrees of freedom, taking advantage of the separation of space and time. The method yields compact symbolic equations of motion with implicit account of the constraints. The general and automatic framework facilitates the creation and manipulation of models with various levels of complexity by adding or removing degrees of freedom. The symbolic treatment allows for analytical gradients and linearized equations of motion. The linear and nonlinear equations can be exported to Python code or dedicated software. There are multiple applications, such as time domain simulation, stability analyses, frequency domain analyses, advanced controller design, state observers, and digital twins. In this article, we describe the method we used to systematically generate the equations of motion of multibody systems and present the implementation of the framework using the Python package SymPy. We apply the framework to generate illustrative land-based and offshore wind turbine models. We compare our results with OpenFAST simulations and discuss the advantages and limitations of the method. The Python implementation is provided as an open-source project.

Branlard, Emmanuel (ORCID:0000000277506128)↗
DOE OSTI2023

AdditiveFOAM

AdditiveFOAM is a continuum heat transfer and fluid flow code for metal additive manufacturing developed on the OpenFOAM CFD Framework. The main components of AdditiveFOAM include: a dynamic heat source model representing heat input from independently moving beams; a robust and efficient thermodynamic solver for solid-liquid phase change in metal alloys; a library to export thermal data to ExaCA— a cellular automata (CA) code used for predicting solidification grain growth. By integrating these capabilities, AdditiveFOAM offers valuable insights into the process-structure relationships of metal additive manufacturing components.

Coleman, John [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2025

Lessons Learned from Three Agrivoltaic Installations in New Jersey

Agrivoltaics is a new technology that has the potential to positively impact commercial farming by combining agricultural practices with the generation of solar energy. While some yield reduction is to be expected, resulting from less sunlight reaching the plant canopy and ground occupied by support structures, the generated electricity provides a low-risk supplemental income to farmers. In order to combine farming with electricity generation, agrivoltaic systems use a lower ground coverage ratio compared to normal solar farms and the PV panels are often mounted higher above the ground in order to facilitate the movement of agricultural equipment and to reduce the contrast between shaded and non-shaded areas. With funding provided from the state of New Jersey and the New Jersey Agricultural Experiment Station (NJAES), we designed and installed three unique agrivoltaic research systems at Rutgers/NJAES farms. These projects were recently completed and are generating electricity that is exported to the grid. This paper discusses the lessons we have learned along the way, including all the steps necessary to see an agrivoltaic project through to completion.

Both, A. J. (ORCID:0000000150845296)↗
DOE OSTI2016

NGEE Arctic TIR and Digital Photos, Drained Thaw Lake Basin, Barrow, Alaska, July 2015

Forward-looking infrared (FLIR) thermal infrared (TIR), digital camera photos, and plot notes across the Barrow, Alaska DTLB_2 site. Data were collected together with measurements of canopy spectral reflectance (see associated metadata record (NGEE Arctic HR1024i Canopy Spectral Reflectance, Drained Thaw Lake Basin, Barrow, Alaska, July 2015 https://doi.org/10.5440/1472053). Data contained within this archive include exported FLIR images (analyzed with FLIR-Tools), digital photos, TIR report, and sample notes. Further TIR image analysis can be conducted in FLIR-Tools. The dataset contains JPG images, PDF, Excel, and CSV files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Assessing the interactions among U.S. climate policy, biomass energy, and agricultural trade

Energy from biomass is potentially an important contributor to U.S. climate change mitigation efforts. However, an important consideration to large-scale implementation of bioenergy is that the production of biomass competes with other uses of land. This includes traditionally economically productive uses, such as agriculture and forest products, as well as storage of carbon in forests and non-commercial lands. In addition, in the future, biomass may be more easily traded, meaning that increased U.S. reliance on bioenergy could come with it greater reliance on imported energy. Several approaches could be implemented to address these issues, including limits on U.S. biomass imports and protection of U.S. and global forests. This paper explores these dimensions of bioenergy’s role in U.S. climate policy and the relationship to these alternative measures for ameliorating the trade and land use consequences of bioenergy. It first demonstrates that widespread use of biomass in the U.S. could lead to imports; and it highlights that the relative stringency of domestic and international carbon mitigation policy will heavily influence the degree to which it is imported. Next, it demonstrates that while limiting biomass imports would prevent any reliance on other countries for this energy supply, it would most likely alter the balance of trade in other agricultural products against which biomass competes; for example, it might turn the U.S. from a corn exporter to a corn importer. Finally, it shows that increasing efforts to protect both U.S. and international forests could also affect the balance of trade in other agricultural products.

Wise, Marshall A.↗
DOE OSTI2024

Effects of Interactions Between Produced Formation Fluid and Rock Matrix on Pore Structure of Caney Shale, Southern Oklahoma

ABSTRACT: Rock-fluid interactions change properties of shales during exploitation. To investigate effects of rock-fluid interactions on pore structure of shales matrix after hydraulic fracturing, powder samples from two late Mississippian Caney Shale cores in the Ardmore Basin, southern Oklahoma, were used to react with formation produced fluid from the field in the batch reactor analysis. X-ray diffraction for mineralogy and Low-pressure nitrogen adsorption isotherms for pore structure were measured for original, after-7days, and after-30days samples. Results show that the samples consist mainly of quartz, followed by clay minerals, carbonates, and feldspar. The pore sizes of micropore (<2 nm) and mesopore (2-50 nm) increase 14%-233% due to dissolution of pyrite, feldspar, and carbonates after 7 days. Due to the transformation from smectite to illite and the increase of pore size, the specific surface area (SSA) decreases after 7-days interactions. After 30-days interactions, the micropore volume slightly increases and the mesopore and macropore volume decreases. Due to the decrease of pore size, the SSA of 30-days reacted samples increases correspondingly and is lower (for the clay-rich sample) or higher (for the calcareous sample) than that of the unreacted samples. Findings improve our understanding of dynamic alteration of shale properties during production. 1. INTRODUCTION Energy demand will continuously grow owing to the increasing global population as well as energy consumption (EIA, 2023). On the other hand, shale gas and oil reshaped the energy market in the United States, enabling the United States to become a net-export of natural gas country in 2017 (EIA, 2023). However, shale reservoirs are challenging tight formations that are still poorly understood in the extraction and production of hydrocarbons (Ross and Bustin, 2009; Curtis et al., 2012; Xiong et al., 2015, 2021a; Li Y. et al., 2016; Gong et al., 2019a; Benge et al., 2021; Awejori et al., 2022; Huang et al., 2022). One of the most challenging topics is the rock-fluid interactions post hydraulic fracturing and its subsequent impacts on the pore structures of fractured formation matrix.

Xiong, Fengyang↗
DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗
DOE OSTI2024

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗
DOE OSTI2025

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2025

Eucalyptus – An Analysis Suite for Fault Trees with Uncertainty Quantification

Eucalyptus is a novel code developed at Lawrence Livermore National Laboratory to incorporate uncertainty quantification into Fault Tree Analysis (FTA). This tool addresses the challenge of imperfect knowledge in “grey-box” systems by allowing analysts to incorporate and propagate uncertainty from component-level assessments to system-level effects. Eucalyptus facilitates a consistent evaluation of the impact of subject matter expert judgment and knowledge gaps on overall system response by Monte Carlo generation of possible system fault trees, sampling probabilities of the existence of subsystems and components. Here, the code supports the specification of fault trees through text and allows export to various formats, including auto-generated images, easing analysis and reducing errors. It has undergone extensive verification testing, demonstrating its reliability and readiness for deployment, and leverages on-node parallelism for rapid analysis. Example analyses are shown that include the identification of system failure paths and quantification of the value of further information about system components.

Fault Tree Analysis↗
DOE OSTI2026

Updating PV and Battery Bill Savings Calculations for Net Billing: New Best Practices for Input Data and Uncertainty

Jurisdictions are increasingly adopting compensation structures for distributed PV and PV-battery systems that price exported energy lower than energy consumed onsite (net billing rates). Standard methods for calculating the bill savings from PV and PV-battery systems were developed for net metering structures, and applying these same methods to net billing structures (such as using Typical Meteorological Year weather with actual year load) introduces bias errors that underestimate PV-battery system bill savings by between 1.5\% and 9\%, depending on the utility rate. We assess the magnitude of these errors and compare them to other sources of uncertainty when estimating the bill savings from PV and PV-battery systems under more complex utility rates.

14 SOLAR ENERGY↗
DOE OSTI2019

Mercury reallocation in thawing subarctic peatlands

Warming Arctic temperatures have led to permafrost thaw that threatens to release previously sequestered mercury (Hg) back into the environment. Mobilisation of Hg in permafrost waters is of concern, as Hg methylation produced under water-saturated conditions results in the neurotoxin, methyl Hg (MeHg). Thawing permafrost may enhance Hg export, but the magnitude and mechanisms of this mobilisation within Arctic ecosystems remain poorly understood. Such uncertainty limits prognostic modelling of Hg mobilisation and impedes a comprehensive assessment of its threat to Arctic ecosystems and peoples. Here, we address this knowledge gap through an assessment of Hg dynamics across a well-studied permafrost thaw sequence at the peak of the growing season in biologically active peat overlying permafrost, quantifying total gaseous mercury (TGM) fluxes, total mercury (Hg Tot ) in the active layer peat, porewater MeHg concentrations, and identifying microbes with the potential to methylate Hg. During the initial thaw, TGM is liberated, likely by photoreduction from permafrost where it was previously stored for decades to centuries. As thawing proceeds, TGM is largely driven by hydrologic changes as evidenced by Hg accumulation in water-logged, organic-rich peat sediments in fen sites. MeHg in porewaters increase across the thaw gradient, a pattern coincident with increases in the relative abundance of microbes possibly containing genes allowing for methylation of ionic Hg. Findings suggest that under changing climate, frozen, well-drained habitats will thaw and collapse into saturated landscapes, increasing the production of MeHg and providing a significant source of the toxic, bioaccumulative contaminant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The effects of storage on the net calorific value of wood pellets

The wood pellet export from Canada to Europe has been increasing steadily in recent years (roughly 1.8 million ton in 2013). Due to distances involved, wood pellets remain in transit and storage for months before their final consumption. The net calorific value determines the price of wood pellet purchase in Europe. There have been concerns about the changes of net calorific values over time. In this study, the effects of storage time, storage configuration, storage temperature, and wood pellet quality on the net calorific value of wood pellets for a period of 6 months were investigated. Storage configurations were open or closed and storage temperatures were 25 °C, 35 °C and 45 °C. Two types of wood pellets used were whitewood and mixed. The results in closed storage indicated that storage time had a positive effect on the net calorific value where the net calorific value increased by 1% to 2% over the storage period. In open storage, the moisture content had the most significant impact on the net calorific value. The net calorific values of the two types of wood pellets were found to be significantly different at p < 0.001. A multivariable linear regression and analyses of variance performed verified the graphical results. Lastly, the authors postulated that the higher energy potential compounds, such as aldehyde and ketone, produced during pellet storage, caused the increase in net calorific values.

09 BIOMASS FUELS↗
DOE OSTI2015

Visualization and functional dissection of coaxial paired SpoIIIE channels across the sporulation septum

SpoIIIE is a membrane-anchored DNA translocase that localizes to the septal midpoint to mediate chromosome translocation and membrane fission during Bacillus subtilis sporulation. Here we use cell-specific protein degradation and quantitative photoactivated localization microscopy in strains with a thick sporulation septum to investigate the architecture and function of the SpoIIIE DNA translocation complex in vivo. We were able to visualize SpoIIIE complexes with approximately equal numbers of molecules in the mother cell and the forespore. Cell-specific protein degradation showed that only the mother cell complex is required to translocate DNA into the forespore, whereas degradation in either cell reverses membrane fission. Our data suggest that SpoIIIE assembles a coaxially paired channel for each chromosome arm comprised of one hexamer in each cell to maintain membrane fission during DNA translocation. We show that SpoIIIE can operate, in principle, as a bi-directional motor that exports DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Structural and biochemical analyses of the DEAD-box ATPase Sub2 in association with THO or Yra1

mRNA is cotranscrptionally processed and packaged into messenger ribonucleoprotein particles (mRNPs) in the nucleus. Prior to export through the nuclear pore, mRNPs undergo several obligatory remodeling reactions. In yeast, one of these reactions involves loading of the mRNA-binding protein Yra1 by the DEAD-box ATPase Sub2 as assisted by the hetero-pentameric THO complex. To obtain molecular insights into reaction mechanisms, we determined crystal structures of two relevant complexes: a THO hetero-pentamer bound to Sub2 at 6.0 Å resolution; and Sub2 associated with an ATP analogue, RNA, and a C-terminal fragment of Yra1 (Yra1-C) at 2.6 Å resolution. We found that the 25 nm long THO clamps Sub2 in a half-open configuration; in contrast, when bound to the ATP analogue, RNA and Yra1-C, Sub2 assumes a closed conformation. Both THO and Yra1-C stimulated Sub2’s intrinsic ATPase activity. We propose that THO surveys common landmarks in each nuclear mRNP to localize Sub2 for targeted loading of Yra1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗