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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

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Environmental Performance Report 2025: Annual Site Environmental Report per the U.S. Department of Energy Order 231.1B Chg 1

The National Laboratory of the Rockies (NLR) Environmental Performance Report provides a description of the laboratory's environmental management activities in calendar year 2025, including information on environmental performance, environmental compliance activities and status, and environmental protection programs, highlights, and successes. The purpose of this report is to ensure that the U.S. Department of Energy (DOE) and the public receive timely, accurate information about events that have positively affected or could adversely affect the health and safety of the public or workers, the environment, or the operations of DOE facilities. This report meets the DOE requirements of the Annual Site Environmental Report (ASER) and has been prepared in accordance with DOE Order 231.1B Chg 1, Environment, Safety and Health Reporting.

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Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Towards a Circular Economy for PET Bottles in the U.S. - 4P Framework

The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.

circular economy↗

State of Innovation 2024: Paving the Way for Low-Carbon Cement and Concrete

Concrete production in the U.S. accounted for nearly 393 million cubic yards in 2023, with $38.8 billion in revenue. While cement, the key ingredient in concrete, is only 10%-15% of concrete's mixture by mass, 8% of total global emissions come from the production of cement. A significant challenge lies in the fact that roughly 51% of concrete emissions stem from the material calcination process of cement production. Stakeholders ranging from cement producers to government agencies are beginning to take measures to significantly reduce concrete emissions by 2050 and are seeking novel technologies from the startup community. Strategies to lower carbon emissions include reducing quantities of cement in concrete formulas; optimizing digital and automated production; lower temperature processing; carbon capture, utilization, and durable storage; and other cost-saving approaches to energy and material efficiencies. New materials based on carbon mineralization and novel cement chemistries hold the potential to reach net-zero or even carbon-negative concrete production; however, there is presently no readily available substitute that can replicate concrete's unique properties and versatility at the volume demanded by construction worldwide. The nature of concrete's raw materials, diverse applications, and scale of demand means that complete decarbonization will rely on a combination of innovative production methods and novel cement chemistries. Low-carbon solutions will need to compete economically with traditional concrete to become viable in a high-volume commodity market, although consumer demand and regulation will play important roles. Despite these challenges, this analysis reveals that venture capital (VC) investments in low-carbon concrete reflect a growing awareness of the decarbonized cement market opportunity. Between 2022 and 2023 emerging low-carbon technologies garnered more than $700 million in VC investments, representing a growing share of investment in the built environment. An investment gap appears after Series A for technology solutions, demonstrating the sector's potential, as well as the need for additional performance assurance and technology incubation.

cement↗

A Primer on Using Analysis to Guide Plastic Circularity

BOTTLE, funded by DOE's Advanced Materials & Manufacturing Technologies Office and Bioenergy Technologies Office (BETO), conducts analysis-guided R&D to change the way we recycle plastics. But what does analysis really mean? In this webinar, BOTTLE Analysis Co-Lead Dr. Taylor Uekert, a researcher with the National Renewable Energy Laboratory (NREL), will introduce key analysis techniques such as techno-economic analysis, life cycle assessment, and environmental justice evaluation. Relevant to both analysts and non-analysts, Dr. Uekert will cover the basics of analysis techniques and discuss how these methods are conducted and interpreted. She will provide examples from the BOTTLE portfolio demonstrating their use in benchmarking and optimizing the costs and environmental impacts of new innovations in plastic redesign and recycling. If you are working in the plastics recycling field - from experimental work to analysis to community-focused projects - you won't want to miss this talk. The webinar will end with a Q&A session.

analysis↗

Paper and Plastics in Landfills: The Missed Opportunity

Landfilling paper and plastic waste represents missed opportunities for resource and energy recovery and significant loses in market value and disposal costs. More paper and plastics are landfilled than previously thought which highlights opportunities for improvement.

disposal cost↗

Environmental Performance Report 2023: Annual Site Environmental Report per the U.S. Department of Energy Order 231.1B Chg 1

The National Renewable Energy Laboratory's (NREL's) Environmental Performance Report provides a description of the laboratory's environmental management activities in calendar year 2023, including information on environmental and sustainability performance, environmental compliance activities and status, and environmental protection programs, highlights, and successes. The purpose of this report is to ensure that the U.S. Department of Energy (DOE) and the public receive timely, accurate information about events that have positively affected or could adversely affect the health and safety of the public or workers, the environment, or the operations of DOE facilities. This report meets the DOE requirements of the Annual Site Environmental Report (ASER) and has been prepared in accordance with DOE Order 231.1B Chg 1, Environment, Safety and Health Reporting.

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Materials Data Science Ontology(MDS-Onto): Unifying Domain Knowledge in Materials and Applied Data Science

Ontologies have gained popularity in the scientific community as a way to standardize terminologies in organizations’ data. Although certain cohorts have created frameworks with rules and guidelines on creating ontologies, there exist significant variations in how Materials Science ontologies are currently developed. We seek to provide guidance in the form of a unified automated framework for developing interoperable and modular ontologies for Materials Data Science that simplifies the ontology terms matching by establishing a semantic bridge up to the Basic Formal Ontology(BFO). This framework provides key recommendations on how ontologies should be positioned within the semantic web, what knowledge representation language is recommended, and where ontologies should be published online to boost their findability and interoperability. Two fundamental components of the MDS-Onto framework are the bilingual package called FAIRmaterials for ontology creation and FAIRLinked, for FAIR data creation. To showcase the practical capabilities of FAIRmaterials, we present two exemplar domain ontologies of MDS-Onto: Synchrotron X-Ray Diffraction and Photovoltaics.

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Building partnerships for development of sustainable energy systems with atmospheric measurements

Atmospheric dynamics often play a critical role in the sustainability and reliability of diverse forms of energy production. This is especially true for the growing number of renewable energy deployments that harness aspects of the environment for power production. While the University of Memphis has a strong research background in energy systems, we have little experience working with the Earth and Environmental Systems Science Division (EESSD) and their associated User Facilities. Of particular interest to us is the Atmospheric Science Research and the Atmospheric Radiation Measurement (ARM) user facility to address surface-boundary layer interactions and physical phenomena. One of the major challenges for understanding and developing energy systems and management platforms is accurate modeling/forecasting of atmospheric conditions across disparate spatial and temporal scales. These conditions are often required to understand the lowest levels of the atmospheric boundary layer, but are also important to understand higher atmospheric conditions where aerosols affect cloud development. The objective of this work was to develop partnerships with national laboratories for collaboration on environmental science and its intersection with sustainable energy systems, as well as to leverage the ARM user facility data repositories to enhance our research capabilities in energy systems and their inter-dependence on environmental systems for future engagement with EESSD. Specifically, we accomplished these objectives by (1) developing collaborations with Oakridge National Laboratory ARM Data Science and Integration Group which resulted in student internships, (2) employed ARM data to develope modeling of the atmospheric boundary layer optical turbulence, and (3) optimally-sized large-scale renewable energy systems and their associated energy storage systems with ARM repository data.

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Annual Site Environmental Report for Pantex Plant, Calendar Year 2023

The 2023 Annual Site Environmental Report (ASER) summarizes Pantex’s status, data, and efforts for the environmental compliance, protection, and restoration programs. It has been prepared in accordance with DOE O 231.1B, Environment, Safety and Health Reporting, and DOE O 458.1, Radiation Protection of the Public and the Environment. These orders outline the requirements for environmental protection programs at DOE facilities to ensure that programs fully comply with applicable federal, state, and local environmental laws and regulations, executive orders, and DOE policies.

54 ENVIRONMENTAL SCIENCES↗

2024 OES-Environmental 2024 State of the Science Report, Chapter 5: Stakeholder Engagement for Marine Renewable Energy

Stakeholder engagement is a critical piece of any new development project that affects public or private interests. Effective, thoughtful engagement and participatory activities early in the planning process of a project can help planners and project developers understand local concerns, adjust designs to avoid negative environmental impacts, select the best site for a project, answer questions, reduce delay, enhance opportunities and benefits, and build support for a project (Cuppen et al. 2016; Portman 2009; Wiersma & DevineWright 2014). On the other hand, cursory or inadequate engagement that is viewed as “checking the box” or tokenism is unlikely to be effective, and can result in project failures, diminished trust, strong opposition, or costly, drawn-out processes (Butcher & MacLennan 2020; Garard & Kowarsch 2017; Gill & Rand 2022; Jolivet & Heiskanen 2010; Pizzi et al. 2021; Sterling et al. 2017).

16 TIDAL AND WAVE POWER↗

Xcel Energy’s electric carbon emissions reduction trajectories in the context of 1.5°C and 2°C warming pathways

In 2015 the Paris Agreement established the goals of limiting global average warming to well below 2°C and pursuing efforts to limit warming to below 1.5°C. A large and growing number of scenarios have been developed by the climate research community that explore global energy and emissions pathways that would achieve those goals. We draw on the most recent database of such scenarios to update a previous analysis of Xcel Energy’s emissions reduction goals in light of evolving climate science. We assess the outlook for the role of the US electricity sector in current economy-wide and global emissions pathways and compare it to Xcel Energy’s near-term resource plans to 2030. We find that global scenarios that achieve the 1.5°C goal span a range of US/North America electricity sector emissions reductions by 2030 of about 65-85%. Xcel Energy’s emissions reductions to date have exceeded those of the US electricity sector as a whole, and its projected trajectory to 2030 under current approved resource plans falls within this range. Scenarios achieving the 2°C goal have a wider range of reductions (about 40-85%). In scenarios achieving either goal, electricity sector emissions fall faster than economy-wide emissions, a robust feature of mitigation scenarios, which typically rely on low carbon electricity to achieve climate targets.

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The impact of urban configuration types on urban heat islands, air pollution, CO 2 emissions, and mortality in Europe: a data science approach

The world is becoming increasingly urbanized. As cities around the world continue to grow, it is important for urban planners and policymakers to understand how different urban configuration patterns affect the environment and human health. We aimed at identifying European urban configuration types, based on the Local Climate Zones categories and street design variables from Open Street Map, and evaluating their association with motorized traffic flows, Surface Urban Heat Island (SUHI) intensities, tropospheric nitrogen dioxide (NO 2 ), CO 2 per capita emissions and age-standardized mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low-density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low-density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO 2 exposure were significantly higher in compact high density and open low rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low-density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO 2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Design and optimization of processes for recovering rare earth elements from end‐of‐life permanent magnets

Recovery of rare earth elements (REEs) from end-of-life (EOL) products represents a strategic opportunity to strengthen the domestic supply chain for rare earth elements. This work presents a superstructure-based optimization framework for finding the most economical processing pathway for different EOL rare earth permanent magnets (REPMs). The framework evaluates state-of-the-art technologies across four processing stages—disassembly, demagnetization, leaching and extraction, and precipitation and calcination—using net present value (NPV) maximization and cost of recovery (COR) minimization objectives. A novel bottom-up costing framework for hydrogen decrepitation is also introduced. Two feedstocks were considered: REPMs from EOL hard disk drives (HDDs), and electric and hybrid electric vehicles (EVs and HEVs). While HDD recycling proved unprofitable due to limited feedstock availability, EVs/HEVs were profitable across a range of parameters and cost estimates. Therefore, our findings suggest that the proposed EOL EV/HEV recycling process may be economical and is worthy of further investigation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Supply Chain Energy and Greenhouse Gas Analysis Using the Materials Flows Through Industry (MFI) Tool: Examination of Alternative Technology Scenarios for the U.S. Chemical Sector

Chemical manufacturing is a large and diverse sector of the U.S. economy, with products, fuels, and a wide assortment of materials used daily by both the public and businesses. Currently, several of the largest volume chemicals produced in the United States rely on fossil fuels as a feedstock, energy source, or both. The list of chemicals includes steam cracking products such as ethylene, propylene, benzene, and xylenes as well as products such as ammonia and methanol. The focus for this work is on platform chemicals that are both produced in the largest volume and have a high potential for subsequent processing into more specialized products. In this study, we explore several new pathways that reduce the overall energy consumption and greenhouse gas (GHG) emissions for each product. These pathways include energy efficiency measures applied to existing production methods, the use of bio‐based fuels and/or feedstocks as new production methods, and electrification of high‐energy‐input stages within current production methods. Scenarios for energy demand and GHG reduction were conducted with the National Renewable Energy Laboratory's Materials Flows through Industry tool. Projections of the energy demand and GHG emissions in 2030 and 2050 are included, using grid composition projections from the NREL ReEDS model. The alternative scenarios selected showcase the effect of realistic changes the industry could make, focusing on technologies with a high level of technical readiness.

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