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DOE OSTI2024

Leveraging State Clean Water Revolving Funds to Expand Clean Energy Financing

To meet clean energy goals, states will need significant capital. Federal funding from the Inflation Reduction Act and the Infrastructure Investment and Jobs Act will help, including by capitalizing clean energy state revolving loan funds (RLFs). States can leverage state clean water revolving funds to finance even more clean energy improvements. New York and Pennsylvania have used this innovative mechanism to extend the impact of their clean energy loan programs. For states looking to extend the reach of their clean energy financing programs, the brief: -Explains how each state leveraged their state revolving funds, -Identifies critical success factors for doing so, and -Offers key elements for replicating this model In New York, New York State Energy Research and Development Authority structured a sale of bonds secured by the repayments from a portfolio of residential energy efficiency loans from its Green Jobs – Green New York Program, with the additional support of a guarantee from the state’s clean water revolving fund. The Pennsylvania Treasury Department received a direct investment of funds from Pennsylvania’s clean water revolving fund to support the relaunch of the Keystone Home Energy Loan Program (HELP), which had previously been shuttered due to lack of support funding. From our review of these two case studies, when facilitating state clean water revolving fund transactions to support clean energy lending, the following critical success factors emerged: -Reference to preventing atmospheric deposition resulting from the combustion of fossil fuels in the state’s Clean Water Act Section 319 Nonpoint Source Pollution Management Plan, which sets out that state’s strategy for reducing pollution into state waterways. -Strong relationships and trust between the clean water revolving fund administrator and the state agency administering the clean energy loan program. -Limited funding exposure for the clean water revolving funds—which are generally large and well capitalized—to ensure that any losses experienced by clean water revolving funds would have a negligible impact on the fund’s ability to support core water and wastewater projects. -Willingness, on the part of the clean water revolving fund administrator, to innovate and engage in careful analysis to support transaction structuring, and support from state energy partner organizations. The brief provides case studies of these states’ experiences, critical success factors, and key elements for replicating the model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Clear Sky Toolkit: Decision Support User Guide

The Clear Sky Decision Support Template is a Microsoft Excel-based resource that enables users to screen and prioritize critical facilities for the addition of solar + storage. The Decision Support Template consolidates and streamlines the most relevant resources from the emergency management discipline, the electric utility sector, and national energy research institutions to assist in further site analysis and decision-making. The Decision Support Template is intended for use by local government and private sector decision-makers who aim to mitigate the effects of power outages on critical infrastructure, understand the potential for deploying photovoltaic (PV) and storage solutions on critical facilities, and align emergency management planning processes and utility needs with community resilience objectives. The Decision Support Template is divided into five modules that provide a structured, step-by-step approach users can follow and apply to unique circumstances. This process guides a more thorough and accurate assessment of a site's potential to accommodate a solar + storage system, provide grid benefits to utilities, and support community resilience and disaster mitigation for the broader region. After identifying potentially viable and preferred sites for solar + storage using the Decision Support Template, users should conduct a more detailed evaluation and consultation with a solar professional.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

FEED Study of CarbonCapture Inc DAC and CarbonCure Utilization Technologies Using United States Steel’s Gary Works Plant Waste Heat (Final Report)

The University of Illinois at Urbana-Champaign (UIUC) led this project to produce a front-end engineering design (FEED) study of an advanced Direct Air Capture and Utilization System (DACUS) system that can remove a minimum of 5,000 tonnes/yr net of carbon dioxide from air (based on cradle-to-gate LCA) and utilizing the CO 2 to produce low carbon intensity ready mix concrete. The designed system, if built, would be larger than any currently existing Direct Air Capture (DAC) collector in the U.S. Such carbon capture technologies are critical to meeting the goals of the DOE’s program to accelerate climate-critical technology. In addition to the power sector, industrial facilities for the manufacture of steel and cement/concrete are among the major sources of anthropogenic CO 2 . DAC is a promising new technology for reducing CO 2 , a potent greenhouse gas, in the atmosphere but is expensive, in part due to the energy required to adsorb and desorb captured CO 2 during cycles. By integrating CarbonCapture Inc. (CCI) DAC modules at United States Steel's Gary Works (USS) and utilizing the site's waste heat, energy, and location this project evaluates the feasibility of utilizing the captured CO 2 and the logistics of transportation. CarbonCapture Inc. has developed an innovative DAC system using novel adsorbents to cost-effectively capture CO 2 . The captured, liquified gas will be trucked to ready-mix concrete plants within the region, the closest of which is approximately 3.5 miles away, where CarbonCure will inject it into concrete during the mixing process at the facilities. The carbon dioxide reacts with concrete, mineralizing into calcium carbonate (CaCO 3 ), permanently locking the greenhouse gas into the matrix of the building material. This FEED study demonstrated a full CO 2 value chain for DACUS from industrial facilities. It also provided a means for Visage Energy Corp. (Visage) to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice. The project team also included Sargent & Lundy (S&L) to provide the constructability review and costing of the integration of the DAC with the steel plant. Ecotek Engineering USA, LLC designed the outside battery limit (OSBL) infrastructure to connect the DAC and the plant. Activities performed during the project included: (1) Project Management Plan; (2) Technology Maturation Plan (TMP); (3) Initial Workforce Readiness Plan; (4) Workforce Readiness Plan; (5) Front-End Engineering Design (FEED) Study; (6) Project Design Basis; (7) Hazards and Operability (HAZOP) Study; (8) Constructability Review; (9) Project Cost Assessment; (10) Logistics Analysis of CO 2 Transportation to the Utilization Site; (11) Business Case Analysis; (12) Life Cycle Analysis (LCA); (13) Environmental Health and Safety (EH&S) Analysis; (14) Environmental Justice Analysis; and (15) Economic Revitalization and Job Creation Outcomes Analysis. This report provides a summary of the outcomes and results of the project, which was performed between Oct. 1, 2022, through Sept. 30, 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

The Dual-Axis Radiographic Hydrodynamic Test Facility Capability eXpansion (DCX) Strategy

This document details the strategy proposed to meet the National Nuclear Security Administration (NNSA) requirement for the Dual-Axis Radiographic Hydrodynamic Test (DARHT) Facility Sustainment and Modernization projects identified in multiple NNSA Stockpile Stewardship and Management Plan (SSMP) reports to Congress [NNSA, 2020; 2021; 2022; 2023; 2024]. DARHT has become indispensable for the certification of the primaries of U.S. nuclear weapons since the current U.S. moratorium halted underground nuclear testing more than 30 years ago. However, aging facilities, evolving technology, and other issues are limiting or threatening the capability of DARHT to meet NNSA’s expanding mission needs now and into the future. This DARHT Capability eXpansion (DCX) strategy was developed to address NNSA needs by extending DARHT’s reliability and resilience, increasing the quality and quantity of DARHT data, and enabling hydrodynamic measurements in complex environments. The strategy can be implemented through integration of line-item projects, acquisition of major items of equipment, and other actions coordinated with the execution of the SSMP. This strategy document is intended for U.S. Government officials, particularly authorizers, appropriators, and program leaders. It may also be furnished to DARHT users, customers, collaborators, stakeholders, and visitors as needed

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Financial Analysis of the High Flow Experiment conducted at the Glen Canyon Dam during Water Year 2023

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specified criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report examines the financial implications of the high flow experiment (HFE) conducted at GCD during the spring of Water Year (WY) 2023 as required by the LTEMP HFE Protocol. This report is part of a series of reports that describe the financial costs of LTEMP experimental releases since the 2016 ROD was adopted in January 2017. Previous reports analyzed the impact of several past HFEs and Bug Flow Experiments. This report focuses on the HFE conducted in April 2023. For this experimental release, financial costs of approximately $1.33 million were incurred because the HFE required sustained water releases exceeding the power plant’s maximum turbine flow rate. In addition, during the experiment, operators were not allowed to shape GCD power production, either to follow Firm Electric Service (FES) customer day-ahead energy deliveries or to respond to market prices. This study identifies the main factors contributing to the HFE costs and examines the interdependencies among these factors. It applies an integrated set of tools to estimate Western Area Power Administration (WAPA) financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the operations that actually occurred and (2) a “Without Experiment” case that simulates operations under the assumption that the HFE did not occur. The “With Experiment” case mimics operations during the HFE and the entire month the HFE occurred. It complies with LTEMP hourly and daily operating criteria. The “Without Experiment” case assumes that the HFE did not occur. The monthly water release volume is assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices. In addition to estimating the financial impact of the HFE, the team used the CRiSPPy model to gain insights into the interplay among ROD operating criteria, exceptions made to criteria to accommodate the HFE, and WAPA operating practices.

13 HYDRO ENERGY↗

DOE OSTI2025

Financial Analysis of the Smallmouth Bass Flows implemented at the Glen Canyon Dam during Water Year 2024

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specifies criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report presents a financial analysis of the Smallmouth bass (Micropterus dolomieu) (SMB) flows implemented at GCD during Water Year (WY) 2024. These bypass flows were introduced by the U.S. Bureau of Reclamation (USBR) as an emergency response to the growing threat posed by invasive SMB in the Colorado River ecosystem downstream of the dam. SMB are a non-native predatory species that pose a significant threat to native fish populations, including the endangered humpback chub (Gila cypha). The thermal regime below GCD, typically cold due to hypolimnetic releases from Lake Powell, has historically served as a thermal barrier limiting SMB establishment. However, persistently low reservoir levels in recent years have reduced stratification in Lake Powell, allowing warmer water to be released downstream. This has enabled SMB to spawn successfully below the dam, prompting urgent ecological concerns. To mitigate the risk of SMB proliferation, the USBR implemented a series of bypass flows in WY 2024. Drawn from a lower elevation than the penstocks, the bypass structures released cooler water downstream. These short-duration bypass flows aimed to keep temperatures cool enough to prevent SMB from spawning, thereby reducing the ecological threat posed by this invasive species. Although motivated by ecological objectives, these bypass flows came with financial tradeoffs. Releasing water through the bypass structures instead of the turbines at GCD reduced hydropower generation, resulting in a significantly lower financial position for Western Area Power Administration (WAPA), which is responsible for marketing the electricity produced by the GCD Powerplant. This report analyzes the financial impact of the SMB flows implemented from July to November 2024. These experimental releases led to an estimated financial cost of approximately $18.9 million, primarily driven by the substantial volume of water diverted through the bypass structures. This study applies an integrated set of tools to estimate WAPA financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the water operations that actually occurred, including the SMB bypass flows, and (2) a “Without Experiment” case that simulates operations under the assumption that the SMB flows did not occur. Both cases comply with LTEMP hourly and daily operating criteria, and the monthly water release volumes are assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices.

13 HYDRO ENERGY↗

DOE OSTI2026

Financial Analysis of the Smallmouth Bass Flows implemented at the Glen Canyon Dam during 2025

Ploussard, Quentin [Argonne National Laboratory (A↗

DOE OSTI2025

Cosmological neutrino mass: a frequentist overview in light of DESI

Supplementary material to DESI publication "Cosmological neutrino mass: a frequentist overview in light of DESI" to comply with the data management plan. Data points as well as parabola parameters for each profile likelihood figure are provided.

Chebat, Domitille [CEA Paris-Saclay] (ORCID:000900↗

DOE OSTI2024

MSD CoP Webinar: Accounting for distributive justice in model-based decision support

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Model-based analyses play an ever-increasing role in informing policy and decision-making. However, many large-scale societal challenges unavoidably involve questions about the fair distribution of positive and negative consequences. How are the costs of the energy transition distributed over households and businesses? How are flood risks redistributed under different flood risk management plans? How are the impacts of climate change and climate mitigation distributed over different parts of the world?These kinds of questions play an important role when deliberating public policy, and the lack, in many cases, of clear answers becomes an obstacle to decision-making. At recent COPs, for example, wicked questions about loss and damages and the phase-out versus phase-down of coal became obstacles to global climate action, illustrating the misalignment of the direction of scientific research and decision-makers' information needs. In this talk, I'll explore advances that are being made that enable analysts to start providing grounded model-based answers to questions of distributive justice, as well as argue that analysts should embrace and explicate the normative nature of their work instead of hiding behind the purported neutrality of science. Presenters: Dr. Jan Kwakkel (Delft University of Technology) Moderator(s): Rebecca Saari (MSD CoP Working Group Co-Chair; Univ. of Waterloo), Matt Sparks (Univ. of Waterloo); Sarah Fletcher (MSD CoP Working Group Co-Chair; Stanford University), Juan Moreno-Cruz (Univ. of Waterloo), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 13, 2024 from 1 PM - 2:15 PM ET

Kwakkel, Jan H.↗

DOE OSTI2026

Sensitivity Analysis of Drivers Water Shortage in the Los Angeles Region During Drought

The code and detailed step-by-step instructions for generating the model output data, processing results, and analysis and plotting are provided at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. The PyArtes model is a python adaptation of the Artes model. PyArtes uses many of the same input data and optimization model architecture as Artes. Documentation for the PyArtes model is provided in the Supplement to the paper. The primary data product are simulated monthly water shortages for indoor and outdoor demand under a large ensemble of drought scenarios (>13,000). The droughts are hypothetical and are not based on historical time series data of supply sources - though historical data did help inform ranges explored for supply parameters. Demands are informed by recent 2017-2021 water supply data. Demands used for the model can be accessed at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. Simulations resolve demand for over 90 water providers in the study region. The results report 36 months of water shortage data for each indoor and outdoor demand node. The study also developed a multilayer perceptron (MLP) neural network trained on a subset of the simulated shortage ensemble to emulate worst annual water shortage for a given set of parameter multipliers -- provided the parameter values fall within the ranges sampled in the ensemble. Emulated water shortages for synthetic ensembles are in the MLP-generated shortages folder. The MLP model was used to generate larger ensembles to support Sobol analysis that would have been extremely computationally expensive to simulate. Datasets provided in this repository*: Simulated shortages. These results are used for the analysis for Figures 5, 8, and 9 in the paper, and also to train the MLP emulator. .zip file containing outputs for the 13,312 scenario ensemble. Separate .csv files for indoor and outdoor shortage for each scenario. Rows = demand ids (~100), Columns = months (36) Units = acre-feet/month of shortage (shortage = monthly demand - supply). 1 acft = 1233.48 m^3 .csv files of aggregated shortages derived from the 13,312 ensemble Rows = scenarios (13,312), Columns = demand ids (~100) Units = acre-feet/year (either worst annual shortage or total shortage over the 3-year drought) .csv file of the parameter multipliers scenarios for the ensemble .csv file of the parameter ranges and baseline values the multipliers were applied to MLP-generated shortages. These results are used for Figures 4, 6, and 7 in the paper. mwd higher folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results Emulated shortages. Rows = scenarios, columns = demand ids, units acft Sobol results. Rows = demand ids, columns Sobol (S1, ST, or 95% confidence interval) value for each parameter mwd lower folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results same organization as mwd higher MLP performance: performance metrics (R^2, RMSE, BIAS, MAPE) for the testing subset (20% or 2,662 scenarios) and simulated vs emulated worst year shortage (acre-feet/year) for every demand node, MWD wholesale regions, and the entire study region (LAC). Supporting data for figures. Figure plotting scripts in the associated GitHub repo. These files support analysis and visualization. Geospatial Data used for plotting simulated water shortages and Sobol results. Dictionary of full names for demand nodes in the model and estimates of water supply by source type informed by Artes input files and California Urban Water Management Planning data: https://water.ca.gov/Programs/Water-Use-And-Efficiency/Urban-Water-Use-Efficiency/Urban-Water-Management-Plans *Readme files provided for each folder.

drought↗

DOE OSTI2024

Source Data for Calculations, UV-vis-NIR, and NMR for A Tetrahedral Neptunium(V) Complex

Data associated with the Nature Chemistry publication (DOI: 10.1038/s41557-024-01529-6 ) was made publicly available in a FigShare repository (10.6084/m9.figshare.24309463) to ensure reproducibility and support the PI's commitment to open-science that was included in the data management plan of the project

Niklas, Julie E.↗

DOE OSTI2026

Supporting Data: Structural and Theoretical Assessment of Covalency in a Pu(III) Borohydride Complex

Data associated with the Journal of the American Chemical Society publication (DOI: 10.1021/jacs.4c09888 ) was made publicly available in a FigShare repository (DOI: 10.6084/m9.figshare.26997388) to ensure reproducibility and support the PI's commitment to open-science that was included in the data management plan of the project

Vlaisavljevich, Bess [University of Iowa]↗

DOE OSTI2025

Supporting Data: Computational Investigation of the Chemical Bond between An(III) Ions and Soft-Donor Ligands

Data associated with the Inorganic Chemistry publication (DOI: 10.1021/acs.inorgchem.4c03924) was made publicly available in a FigShare repository (DOI: 10.6084/m9.figshare.28195664) to ensure reproducibility and support the PI's commitment to open-science that was included in the data management plan of the project.

Roy Chowdhury, Sabyasachi [Department of Chemistry↗

DOE OSTI2021

Replication Data for: Elucidating the composition of PtAg surface alloys with atomic-scale imaging and spectroscopy

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.