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DOE OSTI2021

Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB)

The Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB) has been developed as an integral part of Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model to analyze greenhouse gas (GHG) emissions from land use change (LUC) and land management change (LMC) in the context of overall biofuel life-cycle analysis (LCA). CCLUB relies on i) biofuel production scenarios, ii) LUC and LMC scenarios, and iii) emission factors (EF) to generate GHG emissions of LUC and LMC for biofuel production in gram carbon dioxide equivalent (CO2e) per MJ of fuel produced. Figure 1 outlines the calculations and data sources within CCLUB that are described in this document and Table 1 identifies where these data are stored and used within CCLUB, which is built in Microsoft Excel.

09 BIOMASS FUELS↗

DOE OSTI2022

Life-cycle Analysis of Conversion of Post-Use Plastic via Pyrolysis with the GREET Model

In this report, we present an updated LCA of the PTF pathway developed at Argonne. Benavides et al. (2017) analyzed the environmental impact of producing ultra-low sulfur (ULS) diesel fuel from PUP via pyrolysis (the most common PTF technology). We used the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model and collected data from eight PTF companies to assess the potential energy and environmental benefits associated with this technology (Argonne, 2020). We conducted a survey and aggregated the dataset based on the different responses, which included plant capacity, process yields, feedstock composition, material and energy inputs, and outputs, and other parameters. We calculated the energy, greenhouse gas (GHG) emissions, and water consumption of its intermediate product pyrolysis oil and final product PUP-derived ULS diesel and compared the results to those metrics for their conventional counterparts (crude naphtha and petroleum ULS diesel fuel).

10 SYNTHETIC FUELS↗

DOE OSTI2022

Updated Production Inventory for Lithium-Ion Battery Anodes for the GREET® Model, and Review of Advanced Battery Chemistries

The Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model considers lithium-ion batteries with multiple anode materials. Synthetic graphite is the primary anode material used in the previous GREET versions, even as the model offered options to choose a lithium anode and/or a blended anode (blend of synthetic graphite and silicon). Yet, the inventory (material and energy flows) considered for these anodes is dated, and the anode options do not consider natural graphite, which is another important anode material for lithium-ion batteries. This report documents the material and energy flows for natural graphite anode production from raw material extraction to anode production – as incorporated in the updated GREET model. We also present a brief literature review on the current state of inventory for the other three anodes (synthetic graphite, silicon, and lithium), as well as updates made in the recent GREET model on material and energy flows associated with their respective production. Finally, this study provides a summary of advanced battery systems that may be alternatives to LIBs for use in future electric vehicles.

25 ENERGY STORAGE↗

DOE OSTI2022

Summary of Expansions and Updates in GREET ® 2022

The GREET ® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. GREET is a life cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Argonne has expanded and updated the model in various sectors in GREET 2022, and this report provides a summary of the release.

25 ENERGY STORAGE↗

DOE OSTI2023

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Summary of Expansions and Updates in R&D GREET ® 2023

The Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model was developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail), other end-use sectors, and energy systems. Argonne has expanded and updated the model in various areas in R&D GREET 2023. This report provides a summary of the expansions and updates.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Life-Cycle Analysis Datasets for Regionalized Plastic Pathways

The carbon intensity (CI) of producing five different resins – polyethylene terephthalate (PET), high-density polyethylene (HDPE), low-density polyethylene (LDPE), polypropylene (PP), and polyvinyl chloride (PVC) – in four different international regions – United States of America (USA), Western Europe, Middle East and Northern Africa (MENA), and China – is calculated on a cradle-to-gate basis using the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The list of factors that can potentially vary the CI of the five resins in different international regions include the CI of electricity and natural gas (NG) production, steam cracking feedstock mix, propylene sourcing technology mix, terephthalic monomer (TM) mix, use of hydrogen co-product from steam cracking process, and vinyl chloride monomer (VCM) production technology mix.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Development of R&D GREET 2023 Rev1 to Estimate Greenhouse Gas Emissions of Sustainable Aviation Fuels for 40B Provision of the Inflation Reduction Act

The federal Interagency Working Group on sustainable aviation fuels (SAF) tasked Argonne National Laboratory with developing a modified version of the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model based on R&D GREET 2023. The goal of the new GREET version is to simulate the life-cycle greenhouse gas (GHG) emissions associated with seven sustainable aviation fuel (SAF) pathways for consideration under the 40B Provision of the Inflation Reduction Act – Sustainable aviation fuel credit. The Provision includes a new GHG-based tax credit to incentivize SAF production and reduce the costs of these fuels.

02 PETROLEUM↗

DOE OSTI2025

Life Cycle Analysis of Greenhouse Gas Emissions of Clean Fuels with the R&D GREET 2024 Model

This document summarizes research on the life cycle greenhouse gas (GHG) emissions rates from the production and use of clean fuels to support a new version of the Research and Development Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (R&D GREET) model, R&D GREET 2024 In this effort, Argonne National Laboratory (ANL) focuses on clean fuel pathways that are readily available in the market or are emerging in the near term. The selected pathways represent clean fuel technologies that convert biomass- and/or waste-based feedstocks to liquid and/or gaseous fuels for the transportation sector and other potential uses. The pathways are configured in R&D GREET 2024 with up-to-date feedstock-to-fuel life cycle inventory (LCI) data. Additionally, a new tab has been added to R&D GREET 2024 called “Clean Fuels” which allows the user to easily change inputs and access LCA results. Argonne does not warrant that the results presented in this report are consistent with the requirements of any particular regulatory or incentive program. Users interested in specific programs that reference GREET are encouraged to review guidance specific to those programs if and when it is available to determine appropriate means of compliance and contact the relevant responsible agencies for those specific policies or programs.

09 BIOMASS FUELS↗

DOE OSTI2025

Summary of Expansions and Updates in R&D GREET ® 2024

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Summary of Expansions and Updates in R&D GREET® 2024 Rev.1

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Development of the Well-to-Wake Life Cycle Assessment Model for Marine Fuels in R&D GREET 2025

The Marine analysis capabilities in the 2025 Research and Development Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) have been updated to incorporate the latest findings from the Fourth International Maritime Organization (IMO) GHG Study.1 To support these updates and enhance user flexibility, the former single marine module used in previous R&D GREET versions has been split into two workbook tabs: The Marine_Fuel tab, which covers the fuel-cycle, and the Marine_Trip tab, which covers the trip-cycle. In the Marine_Fuel tab, fuel cycle results for 39 marine fuels are available—assuming a slow speed diesel engine—and can be seen in Appendix A. However, there are options for changing feedstocks for multiple fuels, ability to view results with or without pilot fuels for fuels such as methanol and ammonia, and carbon capture options. All these combinations make the number of total possible pathways over one hundred. For each pathway, life cycle emission results are divided into feedstock, conversion, and combustion categories, along with pilot fuel supply chain emissions for fuels used in dual fuel engines. In the newly created Marine_Trip tab, users can view the life cycle emissions of using these fuels from a trip perspective. Compared to R&D GREET 2024, 16 new types of vessels are added in R&D GREET 2025. Examples of results assuming the default size for each vessel type are available in Appendix A. Additional information categories on vessels are included such as vessel size, main propulsion type, engine power rating, combustion cycle, etc. based on the Fourth IMO GHG Study. Operational mode of the trip, fuel consumption, and load calculation were updated based on the report. The fuel consumption calculation also incorporates low-load adjustment, speed–power correction, weather correction, and fouling correction factors. Furthermore, fuel consumption in boilers or steam turbines is also added for the first time, besides fuel use in main propulsion engines and auxiliary engines. This effort makes the R&D GREET Marine capabilities more robust than before. Users will be able to estimate fuel consumption more accurately for more diverse choices of vessel categories, vessel sizes, and energy converters.

09 BIOMASS FUELS↗

DOE OSTI2025

Summary of Expansions and Updates in R&D GREET® 2025

The research and development (R&D) version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model, or R&D GREET, is developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in all transportation sub-sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy technology systems. Argonne has expanded and updated the model in many areas in R&D GREET 2025. This report provides a summary of the expansions and updates. R&D GREET is designed as an attributional LCA model, but specific consequential effects for certain pathways are included by default when they are scientifically important and/or highly policy relevant. For example, two major consequential elements – induced land use change (ILUC) for biofuels and avoided emissions for certain RNG-based pathways – are implemented by default in R&D GREET because they are highly relevant to our user base and crucial for a comprehensive evaluation of the environmental effects of these technologies. In a future version of R&D GREET, these consequential elements for biofuels and RNG could be more clearly distinguished from core attributional results. We will consider adding a highly visible toggle that would allow users to turn off or adjust these consequential impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Vehicle-Cycle Inventory for Type C School Buses & Intra-City Transit Buses

This report documents the new inventory incorporated into the Research and Development version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) 2025 model for the vehicle cycle of Type C school buses and intracity transit buses. The transportation sector contributes significantly to the United States’ energy consumption and resultant emissions (EPA, 2025a). However, public transit plays an important role in mitigating these impacts because it consumes a relatively low amount of energy per passenger (Congressional Budget Office, 2022). Public transit is widely used in the United States; more than 500,000 school buses (EPA, 2025b) and ~75,000 service buses (American Public Transportation Association, 2025) operate in the nation. These are primarily internal combustion engine vehicles (ICEVs) powered by diesel. Original equipment manufacturers (OEMs) are making efforts to electrify U.S. bus fleets by using batteries as a propulsion system to replace internal combustion engines. Electrification can reduce tailpipe emissions, such as particulate matter (with a diameter ≤10 µm [PM 10 ] and with a diameter ≤2.5 µm [PM 2.5 ]) and nitrogen oxides (Jonas et al., 2025; Martinez and Samaras, 2024; EPA, 2025b; Wayne et al., 2009). Hence, any energy and emission impact analysis of public transit must consider both conventional ICEVs and upcoming electric vehicle (EV) options for the school and transit buses that dominate this landscape. To understand the detailed environmental impact profiles of ICEV and EV school and transit buses, it is necessary to conduct a thorough analysis covering both vehicle manufacturing and vehicle use stages. The current literature lacks a detailed vehicle-cycle inventory for school and transit buses, which makes this kind of comparison difficult. To overcome this gap, we developed a comprehensive vehicle-cycle model for school and transit buses in Argonne’s R&D GREET 2025 model. The model is flexible in handling user inputs for key assumptions, such as component weights and material compositions, upstream energy sources for material processing, and vehicle operating parameters, to understand their impacts on energy use and emissions for both school and transit buses. This report is organized as follows: Section 2 provides details on the modeling approach and vehicle specifications (weights and composition of different vehicle components, and vehicle operating parameters) for both school and transit buses. Section 3 provides details on vehicle assembly, disposal, and recycling (ADR) approaches for the two buses. Section 4 includes details about their incorporation into the R&D GREET model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Updates to Anaerobic Digestion Pathways for Animal Manure in R&D GREET 2025 Rev.1

Renewable natural gas (RNG) produced from animal manure can significantly reduce greenhouse gas (GHG) emissions from the transportation sector, but accurate life cycle assessment (LCA) of this fuel depends on precise modeling of emissions from business-as-usual (BAU) manure manage ment. This report documents updates to the Research & Development version of the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (R&D GREET) model that attempt to improve that precision.

09 BIOMASS FUELS↗

DOE OSTI2026

Updating the Default Anaerobic Digester Technology for Wastewater Sludge Anaerobic Digestion Pathways in R&D GREET 2025 Rev.1

The Greenhouse Gases, Regulated Emissions and Energy Use in Technologies model (R&D GREET) evaluates the life cycle impacts of renewable fuels and materials, including renewable natural gas (RNG) produced from wastewater (WW) sludge. In the sludge-to-RNG pathway, the assumed anaerobic digestion (AD) technology impacts results, such as energy use, greenhouse gases (GHG), and air pollutant emissions. Prior versions assumed sludge was fed through a thermal hydrolysis stage preceding the mesophilic AD (Thermohydrolysis). Such a process is expected to yield biosolids with sufficiently reduced pathogens to qualify for U.S Environmental Protection Agency (EPA) Class A designation. Other technologies, such as mesophilic AD without any advanced pretreatments, typically produce lower quality Class B biosolids but requires a lower energy burden and infrastructure investment. Table 1 displays the available AD technologies and the assumed resulting EPA biosolids class type from each technology. Full descriptions of each technology and their performance differences can be found in previous work.

09 BIOMASS FUELS↗

DOE OSTI2027

Design and Integration of High Precision Superconducting Magnet Power Supply Systems

This paper reviews the design and integration approach being taken to power more than 400 superconducting magnets in Electron Ion Collider (EIC) by power supplies ranging from 20V to 400V and 100A to 18kA. A major challenge is to integrate existing legacy power supplies with new high current systems and maximize performance and reduce costs. Successful implementation requires coordinated integration of power convertors, current regulation, quench protection, energy extraction, machine protection, controls and existing accelerator infrastructure.

43 PARTICLE ACCELERATORS↗