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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Space Biotech: Hindsight, Insight, Foresight

Over the past forty years, microgravity has inspired and enabled applications in a wide range of sectors including medicine, materials, computers, communications, and national defense. Trends show that demand for high-tech solutions is increasing in these sectors, solutions that require higher resolution, greater precision, novel materials, innovative processes, and more sophisticated tools. These are areas where microgravity can offer unique capabilities for innovation. The Emerging Space Office (ESO) has engaged in multiple studies over the past year that have found that microgravity RD is one of the most promising technology areas for contributing to economic growth and to NASAs mission. The focus of these studies was on terrestrial markets rather than NASA applications, applied research rather than basic research, and commercial rather than academic investigators. There have been more success stories than are generally appreciated and there are significant areas of promising future potential. Many of the problems that have limited commercial microgravity development in the past are being solved. Microgravity research and development (RD) requires iteration and learning, as rapidly as possible. New technologies enable high throughput and rapid data collection in increasingly small payloads. The International Space Station is in orbit and provides a laboratory that is available 247 at least until 2024. Frequent flights by commercial space providers to and from the ISS now enable the fast learning cycles needed by high-tech industries. Launch costs are decreasing and the ability to return payloads to Earth is increasing. New commercial space laboratories, such as those being developed by SpaceX and Bigelow Aerospace, are in the final stages of development and testing. This ecosystem for microgravity RD has never been available before. These are game-changer conditions for attracting high-tech industries to space for terrestrial, as well as NASA, applications. However, few know that these capabilities are available or how to use them. In aggregate, the potential value for new applications from microgravity RD over the next ten years could add billions of dollars per year in terrestrial applications to the future economy, create new jobs, and generate a wide range of public benefits in medical advances, while broadening the customer base for the emerging space industry.

biotech↗
DOE OSTI2020

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Photoproduction of the b 1 (1235) Meson off the proton at E gamma = 6-12 GeV

The GlueX Experiment at Jefferson Lab directs a linearly polarized photon beam on a liquid hydrogen target surrounded by an almost hermetic detector. The experiment aims to study the meson spectrum in the light-quark sector and search for exotic spin-parity states predicted by lattice QCD calculations. The lightest exotic candidate is the π 1 meson, which is predicted to decay dominantly to b 1 π. In this thesis, we present efforts to characterize the ωπ 0 decay channel of the b 1 meson as precursor to an analysis of the sought-after π 1 exotic state. We present an introduction to the physics involved and an overview of the detector subsystems with a focus on the Barrel Calorimeter gain monitoring system, as part of the service work expected by the GlueX Collaboration. We discuss the data analysis method used and present two frameworks, for angular moments and partial waves analyses. Details of the simulation used to calculate the detector acceptance. A proof of concept partial wave analysis is presented along with experimental angular moments as first step to a full analysis of the angular distribution Our partial wave analysis indicates that both S- and D-waves are needed, in qualitative agreement with theoretical expectations. The cross-section of the omega π 0 channel is extracted to be of the scale of 1 μb in agreement with previous measurements. The differential cross-section indicates the presence of two production processes with p 1 = -5:24 ± 0:04 for 0:25 < -t < 0:95 GeV 2 ~c 2 and p 2 = -1:24 ± 0:05 for 0:95 < -t < 2:0 GeV 2 ~c 2 , which does not agree with results from previous experiments. The s-channel helicity conservation and helicity amplitudes of the b 1 meson are presented as additional experimental observables. Our results confirm that the b1 photoproduction process does not conserve s-channel helicity though they do not align with previous measurements. The helicity amplitude of the omega are extracted to be |F 1 | 2 = 0:3037 ± 0:0003 which does not agree with the expected value of a b 1 decay or results from a previous experiment. Future steps in all these analyses will be continued by a new graduate student in the group, culminating in a publication.

Foda, Ahmed↗
DOE OSTI2020

Analyzing Next-Generation Supply Chains Using the Materials Flows through Industry Tool

The Materials Flows through Industry (MFI) tool is a supply chain modeling tool developed at the National Renewable Energy Laboratory (NREL) with funding from the Department of Energy's Advanced Manufacturing Office. MFI was created to identify and analyze opportunities to reduce the energy and carbon intensities of the U.S. industrial sector (Hanes and Carpenter 2017). In this work, we present an overview of the MFI tool's structure and capabilities, as well as the results of using MFI to analyze a novel NREL-developed process to 'upcycle' PET plastic into higher-value composite materials (Rorrer et al. 2019). This process combines recycled PET (rPET) plastic with inputs that can be derived from biomass, including muconic acid, acrylic acid, and ethylene glycol, to chemically break down the plastic back to its monomers in a process called glycolization. Then, repolymerization and the application of fiberglass yields the valuable glass fiber reinforced plastic (GFRP) composite, a performance material used in the manufacture of wind turbine blades, boat hulls, and other applications. This rPET-derived GFRP was found to have superior strength and fiberglass adhesion compared to conventional GFRP formulations. Our findings indicate that this GFRP production process, were it to be widely commercialized beyond its current lab-scale, could potentially reduce the fossil energy intensity of the GFRP supply chain by between 37% and 58% compared to the conventional method of GFRP manufacture from fossil-derived inputs. We also estimate potential supply chain greenhouse gas (GHG) emissions reductions between 30% and 40% from this process. Scaling these GHG offset estimates up to annual GFRP production in the U.S. would be roughly equivalent to removing between 150,000 and 200,000 vehicles from U.S. roads. These ranges of impact estimates represent the range of differences associated with the various economic allocation methods we have assumed for the intensity contributions from the first life of the PET plastic. Following Shen et al. (2010), we derive economic allocation factors from the current price ratios of clear- and green-colored recycled PET plastic to virgin PET resin ('waste-valuation' approach) or assume them to be zero in a more simplistic allocation ('cutoff' approach). Future work involving the MFI modeling tool will also be discussed, including preliminary results comparing the energy intensity of conventional and bio-based nylons manufacturing. Attendees will also be encouraged to conduct MFI supply chain modeling of their own by requesting a user account on the MFI web application, which is freely available to the public at the following address: https://mfitool.nrel.gov.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗
DOE OSTI2025

Proactive Regulatory Approaches to Electrification and Load Growth: Workshop Report

On July 10 and 11, 2024, Pacific Northwest National Laboratory and RMI led a workshop in Aurora, Colorado, to explore novel and proactive approaches to electrification and load growth while minimizing risks and costs to customers. Over the next decade, a unique opportunity exists to invest strategically in the electricity system to enable electrification across the transportation, industrial, and building sectors and respond to data and technology-based load growth. However, current utility and regulatory planning practices are insufficient to identify and enable the right investments, and work must be done to reduce the risk and decisional uncertainty faced by utility regulatory commissions and utilities. Ensuring timely electrification investments may require new approaches to address risk, uncertainty, prudence, and cost recovery. Understanding the decision-making process and information needs of utilities and regulators is critical. New policies (or application of policies), financial tools, systems analysis, regulatory mechanisms, and enhanced process transparency may be required. The workshop's goal was to identify proactive regulatory approaches for electrification and load growth that minimize costs and risks to customers. Our intention was that the conversations and the resulting solutions and takeaways would be specific and tactical rather than general and theoretical and that together we would create actionable next steps for key actors in the system, including utilities, regulators, thought leaders, researchers, and the U.S. Department of Energy (DOE). This report is intended to provide workshop attendees with a record and summary of the discussion and proposals raised at the workshop and to provide interested entities who did not attend, such as other regulators, policymakers, utilities, and U.S. DOE offices, with an understanding of what was discussed and with ideas to explore in their organizations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2022

High Temperature Steam Electrolysis Process Performance and Cost Estimates

Technology readiness levels (TRLs) of electrolysis systems have dramatically increased in recent years as the interest in clean hydrogen production and decarbonization of transportation, industrial and other sectors increases across the globe. This is especially true of high temperature steam electrolysis (HTSE) / solid oxide electrolysis cell (SOEC) systems which show promise of much higher system efficiencies than other more developed electrolysis technologies. This possibility of higher efficiencies of HTSE / SOEC systems has been previously assumed to be theoretically possible but in recent years it has become less theoretical and more realistic as an increasing amount of suppliers complete lab and pilot tests showing very promising results. Research in the areas of manufacturing techniques, material selection, electrode and electrolyte compositions, and balance of plant size and integration continues at a fast pace as an increasing number of suppliers both internationally and domestically become involved. The advantages of HTSE become more pronounced when HTSE is coupled with nuclear power plants (NPPs). This is because thermal energy produced by the nuclear reactor can be used in a series of heat transfer loops and heat exchangers to vaporize HTSE feedwater, which drastically improves the economics of the process. Idaho National Laboratory (INL) has been very involved in the research and modeling of HTSE systems for a number of years, in collaboration with other national laboratories, academia, and industry stakeholders both on the hydrogen production as well as the hydrogen demand side. The modeling completed over the years on a large variety of projects has led to a wealth of knowledge at INL including in the area of the technoeconomic assessment (TEA) of HTSE systems. TEAs include process modeling of the HTSE systems to calculate system energy requirements and equipment sizing, followed by estimation of capital and operating costs to enable calculation of the levelized cost of hydrogen (LCOH). The TEA work performed has produced incremental improvements and tuning of the methods, assumptions, models, and results of the analyses as well as providing some opportunities for validating these results. The purpose of this document is to record the current baseline HTSE analyses led by INL to show the current status of assumptions and costs of these systems. Given the rapid development of this technology, the variety of suppliers entering the space, and the increasing attention government and industry are giving to such systems, this document may be updated on a periodic basis with updated analysis and assumptions. This document compiles various analyses results and approaches completed over a period of years into a single document to be used as a baseline going forward. It represents what the INL HTSE analysis group assumes to be the internal best estimate of the current operation, costs, and landscape of the HTSE industry state of the art capability for current SOEC technology in an Nth-of-a-Kind (NOAK) plant, which in this study is defined as existence of the manufacturing capacity to support previous deployment of N = 100 count of 25 MWe modular HTSE blocks (with modular equipment component cost reductions specified as following a 95% learning curve). That said, This is a public document and as such so no proprietary data was used or included in this report. There may be HTSE suppliers that have performance specifications, and cost estimates, and test data that differ from the analysis presented in this document. This document is meant to be a best conservative estimate of the technology and not an absolute reference.

08 HYDROGEN↗
DOE OSTI2022

High Temperature Steam Electrolysis Process Performance and Cost Estimates - DOE Hydrogen Program AMR Presentation

Technology readiness levels (TRLs) of electrolysis systems have dramatically increased in recent years as the interest in clean hydrogen production and decarbonization of transportation, industrial and other sectors increases across the globe. This is especially true of high temperature steam electrolysis (HTSE) / solid oxide electrolysis cell (SOEC) systems which show promise of much higher system efficiencies than other more developed electrolysis technologies. This possibility of higher efficiencies of HTSE / SOEC systems has been previously assumed to be theoretically possible but in recent years it has become less theoretical and more realistic as an increasing amount of suppliers complete lab and pilot tests showing very promising results. Research in the areas of manufacturing techniques, material selection, electrode and electrolyte compositions, and balance of plant size and integration continues at a fast pace as an increasing number of suppliers both internationally and domestically become involved. The advantages of HTSE become more pronounced when HTSE is coupled with nuclear power plants (NPPs). This is because thermal energy produced by the nuclear reactor can be used in a series of heat transfer loops and heat exchangers to vaporize HTSE feedwater, which drastically improves the economics of the process. Idaho National Laboratory (INL) has been very involved in the research and modeling of HTSE systems for a number of years, in collaboration with other national laboratories, academia, and industry stakeholders both on the hydrogen production as well as the hydrogen demand side. The modeling completed over the years on a large variety of projects has led to a wealth of knowledge at INL including in the area of the technoeconomic assessment (TEA) of HTSE systems. TEAs include process modeling of the HTSE systems to calculate system energy requirements and equipment sizing, followed by estimation of capital and operating costs to enable calculation of the levelized cost of hydrogen (LCOH). The TEA work performed has produced incremental improvements and tuning of the methods, assumptions, models, and results of the analyses as well as providing some opportunities for validating these results. The purpose of this document is to record the current baseline HTSE analyses led by INL to show the current status of assumptions and costs of these systems. Given the rapid development of this technology, the variety of suppliers entering the space, and the increasing attention government and industry are giving to such systems, this document may be updated on a periodic basis with updated analysis and assumptions. This document compiles various analyses results and approaches completed over a period of years into a single document to be used as a baseline going forward. It represents what the INL HTSE analysis group assumes to be the internal best estimate of the current operation, costs, and landscape of the HTSE industry state of the art capability for current SOEC technology in an Nth-of-a-Kind (NOAK) plant, which in this study is defined as existence of the manufacturing capacity to support previous deployment of N = 100 count of 25 MWe modular HTSE blocks (with modular equipment component cost reductions specified as following a 95% learning curve). That said, this is a public document and as such so no proprietary data was used or included in this report. There may be HTSE suppliers that have performance specifications, and cost estimates, and test data that differ from the analysis presented in this document. This document is meant to be a best conservative estimate of the technology and not an absolute reference.

08 HYDROGEN↗
NASA NTRS2021

AIAA Ascend 2021 Conference On Demand Manufacturing of Electronics Panel Abstract

1. Session Proposal o Session Title NASA’s In Space Manufacturing and the On Demand Manufacturing of Electronics o Session Topic Primary -- Space Logistics, Autonomy, and Robotics; Secondary – Transformative Research and Technologies o Session Format: Panel Discussion. o Requested Session Duration: 60 minutes o Short Session Description: The goal of NASA’s On Demand Manufacturing of Electronics project is to develop and demonstrate the feasibility of a low-gravity, on-demand manufacturing system for flexible hybrid electronic devices on the International Space Station. This panel will feature several key collaborators and team members from the commercial sector, academia, and internal to NASA, each of which are contributing an unique and vital role to the design and implementation of this new technology system. o Extended Session Description (Please describe in detail the activity proposed, including how you intend to use the requested session duration. This session description will be provided to the reviewers for consideration and will not be displayed in the online agenda.): The session will be moderated by Curtis Hill, the Project Lead for the On Demand Manufacturing of Electronics (ODME), and he will start by giving a brief introduction to the ODME project which is working to produce a demo system for the manufacturing of electronic devices on the International Space Station. Panelists consisting of collaborators and team members to the ODME project will then give a brief (~5 min) introduction highlighting their contributions to the project, followed by time for Q&A from the audience. The panel will consist of: 1. Kenneth Church, nScrypt. nScrypt is a leader in multi-material printing with a modular system that incorporates a direct write thick film print head, a polymer fused filament fabrication print head, a laser sintering attachment, a drill head attachment for milling, and a pick and place. The system can print a layer and scan for accuracy of prints. The combination of multiple print heads and scanning allows for the on-demand production of intricate electronic components. 2. Andy Kurk, TechShot, Inc. Techshot, Inc. has collaborated extensively with NASA on the in space manufacturing of both printed electronics and fused metal materials. They are currently working to develop and integrate a test system for printed electronics, and a flight demonstration on the International Space Station is anticipated in 2024. 3. Ed Hendricks, NextFlex. NextFlex has the goal of advancing the manufacture of flexible hybrid electronics in the U.S. They are working with ODME on the development of AstroSense, an additively manufactured, wireless, flexible, and wearable health sensor. 4. Dr. Pradeep Lall, Auburn University. Professor Lall is the MacFarlane Endowed Distinguished Professor in the Department of Mechanical Engineering with a Courtesy Joint Appointment in the Department of Electrical and Computer Engineering and a Courtesy Joint Appointment in the Department of Finance. He is collaborating with NASA’s ODME project to develop multilayer printable devices and to develop techniques to test the quality of a printed electronic device. 5. Dr. Wei Gao, California Institute of Technology. Professor Gao is an Assistant Professor of Medical Engineering. His group is developing fully printed, flexible, and wearable biosensors for crew health monitoring in collaboration with NASA’s ODME project. In addition, they are working on using sweat to power biofuel cells for wearable, self-powered electronic devices. 6. Beth Paquette, NASA Goddard. The ODME branch at NASA Goddard is spearheading a sounding rocket flight demo to prove the capability of a printed electronic device with multiple sensors. In addition, they focus on thin film and flexible energy storage evaluations. o Session Goal(s)/Outcome(s): Please list the learning objectives and/or tangible outcomes (technical paper or other publication). The goal of this session is to highlight the internal and collaborative efforts of NASA’s On Demand Manufacturing of Electronics project to develop a system for printing electronics that will be tested on the International Space Station in 2024. In addition, the session with facilitate discussion with the community on the state of the art of printable electronics, current challenges, and new avenues for collaboration.

Jennifer McInnis Jones↗
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

Integrating Carbon Capture, Utilization, & Sequestration into Chemical Pulp Mills

The U.S. pulp and paper industry presents a unique and largely untapped opportunity for large- scale carbon dioxide removal (CDR). Unlike most industrial sectors, pulp mills rely heavily on biomass, meaning that much of their carbon emissions originate from atmospheric CO₂ that was recently captured by plants. If this biogenic CO₂ can be captured and permanently stored, pulp mills can be transformed from carbon emitters into net carbon removal facilities. This project was motivated by that opportunity and aimed to develop and evaluate integrated, low-cost strategies for capturing, utilizing, and sequestering CO₂ within existing chemical pulping operations. The scope of this work focused on four complementary innovations designed to integrate seamlessly into kraft pulp mill infrastructure: (1) in situ CO₂ capture within the recovery cycle, (2) oxy-fuel retrofitting of the rotary lime kiln to produce a high-purity CO₂ stream, (3) ex situ CO₂ capture and mineralization using pulp mill residues (dregs, grits, and lime mud), and (4) beneficial reuse of these residues as mineral carbonate fertilizers. The project combined process modeling, laboratory experimentation, life cycle assessment (LCA), and field trials to evaluate the technical feasibility, economic viability, and environmental impact of these approaches. The results demonstrate that pulp mills can serve as effective platforms for carbon removal when equipped with integrated carbon capture systems. Process modeling showed that combining sodium spiking with oxy-fuel calcination significantly enhances CO₂ capture efficiency while reducing costs by up to 31% compared to conventional configurations. Experimental work further revealed that calcination behavior in high-CO₂ environments differs substantially from traditional systems, leading to the development of a new kinetic model that predicts reaction rates under these conditions. This model provides essential design guidance for next-generation decarbonized lime kilns. In parallel, the project demonstrated that alkaline mineral residues generated during pulping operations can be repurposed as a sustainable alternative to agricultural lime. Across a wide range of soils in the southeastern United States, these materials performed equivalently to commercial lime in adjusting soil pH while offering lower greenhouse gas emissions and reduced cost. Field and greenhouse studies confirmed that crop and tree growth responses were comparable, supporting their viability as a drop-in replacement. This co-product pathway provides a practical utilization strategy that offsets costs and improves overall system economics. A major contribution of this project is the first comprehensive life cycle assessment of carbon removal in pulp and paper systems across multiple system boundaries. Results show that retrofitted mills can achieve carbon removal efficiencies ranging from 12% to 92%, depending on how the system is defined. This finding highlights a critical issue in carbon accounting: reported performance is highly sensitive to methodological choices. By explicitly quantifying these differences, this work provides valuable guidance for policymakers, carbon registries, and project developers working to standardize carbon removal metrics. From a commercialization perspective, the technologies investigated in this project are well- aligned with existing industrial infrastructure, minimizing the need for entirely new facilities. 3 DE-EE0009413 Industry engagement throughout the project—including collaboration with pulp and paper companies, equipment manufacturers, and carbon removal developers—has accelerated the transition from research to deployment. Notably, a commercial developer is actively pursuing carbon capture projects at pulp mills in the southeastern United States and has cited this research as a contributing foundation. The emergence of voluntary carbon markets and long-term offtake agreements further strengthens the business case for implementation. The broader public benefits of this work are significant. By enabling large-scale carbon removal using existing industrial systems, this approach offers a near-term pathway to reduce atmospheric CO₂ concentrations while supporting domestic manufacturing and rural economies. The reuse of industrial residues as fertilizers reduces reliance on mined materials, lowers costs for farmers, and decreases environmental impacts associated with conventional lime production. In addition, the project has supported workforce development by training graduate students and researchers in carbon capture technologies, helping to build capacity in a critical area of national interest. In conclusion, this project demonstrates that integrated carbon capture, utilization, and sequestration in pulp mills is both technically feasible and economically promising. By combining process innovation, experimental validation, and systems-level analysis, the work advances the understanding of how biomass-based industries can contribute to climate mitigation. The findings provide a strong foundation for commercial deployment and offer a scalable solution for transforming a major U.S. industry into a source of durable carbon removal.

09 BIOMASS FUELS↗
DOE OSTI2023

Final Technical Report

Statement of the problem or situation that is being addressed in your application. The DOE and its national laboratories developed the Home Energy Score™ (HES) to encourage homeowners to improve their energy performance, lower costs and to share energy information through the MLS listing, appraisal, and financing channels. While the HES is an instrumental tool, it is currently underutilized and consists of technical, structural and sector barriers which need to be addressed in order to scale and many energy efficiency contractors are understandably overwhelmed by the added time and effort and lack of incentive to sell and deliver deep retrofit projects while simultaneously meeting the DOE HES program requirements; consequently, contractors may decide to forgo participation. Home Energy Rating System (HERS) Raters have the opportunity to play the critical Assessor role in producing a Home Energy Score (HES); this role has immense potential but currently is unfulfilled. Lastly, while utilities are interested in their customer base achieving greater energy efficiency, especially to help offset growing residential loads in states like California that are accelerating electrification, utilities do not have access to the market actors who are on the front line of influence to homeowners or review and approve their permits: HERS Raters, assessors, contractors and building departments. General statement of how this problem is being addressed: ConSol will integrate the Home Energy Score™ (HES) to its State of California, approved home energy rating services (HERS) platform (CHEERS) to develop a single tool for contractors nationwide to assess, record and install recommended cost, energy, and emissions saving measures to the 140 million single-family homes throughout the U.S. and 14 million homes in California (CHEERS+HES). The CHEERS high fidelity energy code permitting data will be integrated with HES for simple, accurate, easy-to-use home energy estimation and analysis and will directly gain access to the retrofit and renovations markets with the same upgraded platform. This innovative project will assist the utilities in supporting existing homes in their jurisdictions with HES and develop measures to improve energy efficiency and reduce emissions. How is this problem being addressed? What is the overall project approach? In effort to expand the Home Energy Score™ (HES) by increasing the use of aggregable home energy asset data, ConSol proposes to integrate the DOE HES via Application Programming Interface (API) to its State of California approved home energy rating services platform (CHEERS). Once the CHEERS platform and HES are integrated (CHEERS+HES), this enhanced platform will be instantly available and actively deployed via Phase 1 pilot to HERS Raters, assessors and contractors in California to market-test the solution, understand the rate of adoption and identify opportunities for improvement prior to scaling nationally. The CHEERS high fidelity energy code permitting data will be integrated with HES for simple, accurate, easy-to-use home energy estimation and analysis and will directly gain access to the retrofit and renovations markets with the same upgraded platform. This innovative project will assist the building industry and homeowners with an easy-to-use assessment if energy and carbon impacts of existing homes, and assist the utilities in supporting existing homes in their jurisdictions with HES to improve energy efficiency and reduce emissions. What is to be done in Phase I? During Phase I of this proposed project, ConSol will (1) design software architecture that links CHEERS to the Home Energy ScoreTM via API, (2) solicit partnership from one or more California utilities for a regional pilot, (3) test the new software with its HERS Raters and contractor network in the partnership utility jurisdiction, (4) launch a pilot version of the newly developed software with HERS Raters and contractors in the utility territory, and (5) explore California’s GoGreen energy efficiency homeowner lending program in parallel with the pilot. Commercial Applications and Other Benefits. Summarize the future applications or public benefits if the project is carried over into Phase II or Phase III and beyond. The CHEERS+HES commercialized product will be ready for national market scale following a successful Phase 1 performance. The CHEERS+HES adoption is estimated to reach a 5% adoption growth rate versus the 110,000 baseline, starting in Year 1 after Phase I completion, and continuing each year. As a direct benefit to the DOE, CHEERS will set a goal of 100,000 Home Energy Score assessments for existing home alterations within the first 10 years following Phase 1 performance. The technical benefits of this proposed project include the harmonized, automated, and seamless integration of the DOE HES into the widely used and market leading California energy registry, CHEERS. The social benefits include the aggregate energy, cost and GHG savings by allowing the broader public streamlined access to the CHEERS+HES measurement and the energy efficiency recommended measures that may result. Key Words: Home Energy ScoreTM (HES); Application Programming Interface (API); Home Energy Rating Services (HERS); HERS Raters; contractors; assessors; existing homes, energy asset data; cost, energy, and emissions saving measures; energy code (Title 24) compliance; document repository; utilities; pilot; newly developed software; energy efficiency; homeowner. Summary for Members of Congress: The DOE Home Energy Score™ (HES) is a tool to encourage homeowners to improve their energy performance, lower costs and share energy information but is underutilized and consists of barriers which need to be addressed in order to scale. In effort to expand the HES, CHEERS, Inc. will integrate the HES to its State of California, approved home energy rating services (HERS) platform (CHEERS) to develop a single tool for contractors nationwide to assess, record and install recommended cost, energy, and emissions saving measures to the 140 million single-family homes throughout the U.S. and 14 million homes in California.

Application Programming Interface (API)↗
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 OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2020

HarDWR - Cumulative Water Rights Curves

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on Harmonized Water Rights Records v2.0 sourced from WestDAAT - Added "Unspecified" was a water source category, and files associated with this category v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description This product an updated version of the database used as input to the WBM model (Grogan et al. in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (2024). This database contains 2,667 individual .csv files, three for each Water Management Area (WMA) in the 11-state region. File Naming WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either "S" for surface water rights, "G" for groundwater rights, or "U" for unspecified. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the [###] unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al. in review) For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in the study region. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the second index in this object, the data for California will also be in the second index for each accompanying list. wmasRightsPersGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for groundwater. wmasRightsPersSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for surface water. wmasRightsPersUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for water from an unspecified source. wmasRightsTotsGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for groundwater. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for surface water. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for water from an unspecified source. This object is provided for convenience to check out original total values, if desired. wmaIDByState: A list of data frames which contain the by state allocation by WMA matrix. There is a matrix for each state in a different data frame within the object.

Economics↗