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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Challenges and Perspectives in Lignin‐Derived Polyurethane Foam Synthesis

Abstract Polyurethane foams (PUFs) represent a significant segment of the polyurethane (PU) and cellular plastics industries, owing to their versatile applications and desirable properties. However, the production of PUFs heavily relies on petroleum‐derived chemicals, including polyols and isocyanates, raising critical environmental concerns. Lignin, an abundant aromatic macromolecule, offers a promising alternative for replacing petroleum‐based polyols because of its intrinsic hydroxyl groups. While efforts have been made to produce and apply various lignin‐based polyurethane foams (LPUFs), their commercialization remains limited by challenges such as low product consistency, poor technical performances, and high production costs. This study critically evaluates recent advances in the development of LPUFs, including innovative synthesis methods, functional applications, and emerging research trends. Moreover, potential strategies are discussed, such as lignin fractionation, modification, and co‐solvent assistance, for addressing the challenges. By resolving them, LPUFs could play a pivotal role in transitioning the PU industry to help achieve a circular bioeconomy.

Zhang, Mairui [Carl and Melinda Helwig Department ↗
DOE OSTI2024

Multidimensional and multitemporal energy injustices: Exploring the downstream impacts of the Belo Monte hydropower dam in the Amazon

Energy transition technologies, such as hydroelectric dams, have been seen as symbols of progress, modernity, cheap energy, environmental sustainability, and resource abundance, leading to overestimating their benefits and underestimating their drawbacks. In this study, we use the tenets approach of energy justice and a qualitative case study to explore, from a multidimensional and multitemporal perspective, the impacts faced by the inhabitants of a community located downstream from the Belo Monte hydroelectric dam. Through in-depth interviews and observations, data were collected at three points: during the late stage of construction (2016) and early operation (2017, 2019). Furthermore, we found that individuals face multiple and diverse energy injustices at various stages of the dam construction, and its severity changes over time. For instance, distributional issues were more predominant at the beginning of data collection since fisheries, their main livelihood activity was impacted by dam construction. Then, other justice issues, such as capabilities, emerged in the last years of data collection.

13 HYDRO ENERGY↗
DOE OSTI2026

Gene and genome duplications have contrasting impacts on biosynthetic and flower developmental pathways in California poppy

Benzylisoquinoline alkaloids (BIAs) represent a vast group of specialized plant metabolites with diverse pharmaceutical applications, synthesized by a variety of gene families. Among the multiple plant lineages that produce BIAs, the most notable is the poppy family (Papaveraceae), with California poppy (Eschscholzia californica) emerging as a model organism. Here, we report a haplotype-resolved genome assembly, in combination with a high-density expression atlas, for California poppy. Genome analyses reveal recent diversification of BIA biosynthesis genes in poppy through localized duplications. Furthermore, we demonstrate that the degree of phylogenetic relatedness among paralogs within BIA biosynthesis-associated gene families correlates with similarities in gene expression. In contrast, gene families involved in carotenoid biosynthesis, which contributes to the intense orange petal pigmentation, are not phylogenetically clustered, and floral developmental regulators exhibit a high degree of retention of gene duplicates associated with ancient polyploidy events. These findings illustrate alternative roles for gene and genome duplications as drivers of trait evolution. Given the position of California poppy in the angiosperm phylogeny, the high-quality genomic resources generated for this work constitute a valuable resource for comparative genomic and transcriptomic analyses for poppies and flowering plants more generally.

Rössner, Le-Han [Justus-Liebig University, Giessen↗
DOE OSTI2023

The state of food systems worldwide in the countdown to 2030

This Analysis presents a recently developed food system indicator framework and holistic monitoring architecture to track food system transformation towards global development, health and sustainability goals. Five themes are considered: (1) diets, nutrition and health; (2) environment, natural resources and production; (3) livelihoods, poverty and equity; (4) governance; and (5) resilience. Each theme is divided into three to five indicator domains, and indicators were selected to reflect each domain through a consultative process. In total, 50 indicators were selected, with at least one indicator available for every domain. Harmonized data of these 50 indicators provide a baseline assessment of the world’s food systems. We show that every country can claim positive outcomes in some parts of food systems, but none are among the highest ranked across all domains. Furthermore, some indicators are independent of national income, and each highlights a specific aspiration for healthy, sustainable and just food systems. The Food Systems Countdown Initiative will track food systems annually to 2030, amending the framework as new indicators or better data emerge.

Schneider, Kate R.↗
NASA NTRS2011

Evidence Report, Risk of Inadequate Design of Human and Automation/Robotic Integration

The success of future exploration missions depends, even more than today, on effective integration of humans and technology (automation and robotics). This will not emerge by chance, but by design. Both crew and ground personnel will need to do more demanding tasks in more difficult conditions, amplifying the costs of poor design and the benefits of good design. This report has looked at the importance of good design and the risks from poor design from several perspectives: 1) If the relevant functions needed for a mission are not identified, then designs of technology and its use by humans are unlikely to be effective: critical functions will be missing and irrelevant functions will mislead or drain attention. 2) If functions are not distributed effectively among the (multiple) participating humans and automation/robotic systems, later design choices can do little to repair this: additional unnecessary coordination work may be introduced, workload may be redistributed to create problems, limited human attentional resources may be wasted, and the capabilities of both humans and technology underused. 3) If the design does not promote accurate understanding of the capabilities of the technology, the operators will not use the technology effectively: the system may be switched off in conditions where it would be effective, or used for tasks or in contexts where its effectiveness may be very limited. 4) If an ineffective interaction design is implemented and put into use, a wide range of problems can ensue. Many involve lack of transparency into the system: operators may be unable or find it very difficult to determine a) the current state and changes of state of the automation or robot, b) the current state and changes in state of the system being controlled or acted on, and c) what actions by human or by system had what effects. 5) If the human interfaces for operation and control of robotic agents are not designed to accommodate the unique points of view and operating environments of both the human and the robotic agent, then effective human-robot coordination cannot be achieved.

Zumbado, Jennifer Rochlis↗
NASA NTRS2014

Mars Sample Return Using Commercial Capabilities: Mission Architecture Overview

Mars Sample Return (MSR) is the highest priority science mission for the next decade as recommended by the recent Decadal Survey of Planetary Science. This paper presents an overview of a feasibility study for an MSR mission. The objective of the study was to determine whether emerging commercial capabilities can be used to reduce the number of mission systems and launches required to return the samples, with the goal of reducing mission cost. We report the feasibility of a complete and closed MSR mission design using the following scenario that covers three synodic launch opportunities, beginning with the 2022 opportunity: A Falcon Heavy injects a SpaceX Red Dragon capsule and trunk onto a Trans Mars Injection (TMI) trajectory. The capsule is modified to carry all the hardware needed to return samples collected on Mars including a Mars Ascent Vehicle (MAV), an Earth Return Vehicle (ERV), and hardware to transfer a sample collected in a previously landed rover mission to the ERV. The Red Dragon descends to land on the surface of Mars using Super Sonic Retro Propulsion (SSRP). After previously collected samples are transferred to the ERV, the single-stage MAV launches the ERV from the surface of Mars. The MAV uses a storable liquid bi-propellant propulsion system to deliver the ERV to a Mars phasing orbit. After a brief phasing period, the ERV, which also uses a storable bi-propellant system, performs a Trans Earth Injection (TEI) burn. Upon arrival at Earth, the ERV performs Earth and lunar swing-bys and is placed into a lunar trailing circular orbit - an Earth orbit, at lunar distance. A later mission, using Dragon and launched by a Falcon Heavy, performs a rendezvous with the ERV in the lunar trailing orbit, retrieves the sample container and breaks the chain of contact with Mars by transferring the sample into a sterile and secure container. With the sample contained, the retrieving spacecraft makes a controlled Earth re-entry preventing any unintended release of pristine martian materials into the Earth's biosphere. The analysis methods employed standard and specialized aerospace engineering tools. Mission system elements were analyzed with either direct techniques or by using parametric mass estimating relationships (MERs). The architecture was iterated until overall mission convergence was achieved on at least one path. Subsystems analyzed in this study include support structures, power system, nose fairing, thermal insulation, actuation devices, MAV exhaust venting, and GN&C. Best practice application of loads, mass growth contingencies, and resource margins were used. For Falcon Heavy capabilities and Dragon subsystems we utilized publically available data from SpaceX, published analyses from other sources, as well as our own engineering and aerodynamic estimates. Earth Launch mass is under 11 mt, which is within the estimated capability of a Falcon Heavy, with margin. Total entry masses between 7 and 10 mt were considered with closure occurring between 9 and 10 mt. Propellant mass fractions for each major phase of the EDL - Entry, Terminal Descent, and Hazard Avoidance - have been derived. An assessment of the effect of the entry conditions on the thermal protection system (TPS), currently in use for Dragon missions, shows no significant stressors. A useful payload mass of 2.0 mt is provided and includes mass growth allowances for the MAV, the ERV, and mission unique equipment. We also report options for the MAV and ERV, including propulsion systems, crewed versus robotic retrieval mission, as well as direct Earth entry. International planetary protection policies as well as verifiable means of compliance will have a large impact on any MSR mission design. We identify areas within our architecture where such impacts occur. We also describe preliminary compliance measures that will be the subject of future work. This work shows that emerging commercial capabilities as well as new methodologies can be used to efficiently support an important planetary science objective. The work also has applications for human exploration missions that use propulsive EDL techniques

Red Dragon↗
NASA NTRS2024

Central California Disasters: Incorporating Satellite-Derived Precipitation and Soil Moisture Products into Flood Preparedness and Emergency Management in California

Atmospheric rivers are a major contributor to extreme precipitation events and flooding in California. This study assessed the feasibility of using Earth observation data to monitor precipitation, soil moisture, and flooding from atmospheric rivers in the Salinas River Watershed in central California during the winter of 2022-2023. The team analyzed satellite derived precipitation estimates from the Global Precipitation Measurement mission, soil moisture data from the Soil Moisture Active Passive radiometer, and synthetic aperture radar imagery from Sentinel-1 to detect flood inundation. Global Precipitation Measurement precipitation estimates were found to underestimate rainfall by 33% to 52% compared to rain gauge data. The team found the Soil Moisture Active Passive dataset to be a valuable flooding indicator that they could visualize through various graphical representations, although its accuracy still needs verification with in situ flood maps. Sentinel-1 synthetic aperture radar imagery provided mapping of flood inundation extent along the Salinas River and surrounding areas and the Blue Spot model appears to be a good predictor of pluvial flood zones. The findings suggest Earth observations can enhance precipitation and flooding monitoring by the California Department of Water Resources, though further verification is needed. Integration of these datasets with vulnerability indices highlighted communities at highest risk during the 2022-2023 flooding events.

Abhinav Banthiya↗
DOE OSTI2025

A terminology for scientific workflow systems

The term “scientific workflow” has evolved over the last two decades to encompass a broad range of compositions of interdependent compute tasks and data movements. It has also become an umbrella term for processing in modern scientific applications. Today, many scientific applications can be considered as workflows made of multiple dependent steps, and hundreds of workflow systems have been developed to manage and run these scientific workflows. However, no turnkey solution has emerged from the field to address the diversity of scientific processes and the infrastructure on which they are supposed to be implemented. Instead, new research problems requiring the execution of scientific workflows with some novel feature often lead to the development of an entirely new workflow system. A direct consequence of this situation is that many existing workflow management systems (WMSs) share some salient features, offer similar functionalities, and can manage the same categories of workflows but at the same time also have some distinct capabilities that can be important for specific applications. This situation makes researchers who develop workflows face the complex question of selecting a WMS. This selection can be driven by technical considerations, to find the system that is the most appropriate for their application and for the computing and storage resources available to them, or other factors such as reputation, adoption, strong community support, or long-term sustainability. To address this problem, a group of WMS developers and practitioners joined their efforts to produce a community-based terminology of WMSs. This paper summarizes their findings and introduces this new terminology to characterize WMSs. Furthermore, this terminology is composed of fives axes: workflow structure and characteristics, composition, orchestration, data management, and metadata capture. Each axis comprises several concepts that capture the prominent features of WMSs. Based on this terminology, this paper also presents a classification of 23 existing WMSs according to the proposed axes and terms.

Community-based terminology↗
NASA NTRS2012

Global Infrared Observations of Roughness Induced Transition on the Space Shuttle Orbiter

High resolution infrared observations made from a mobile ground based optical system captured the laminar-to-turbulent boundary layer transition process as it occurred during Space Shuttle Endeavour's return to earth following its final mission in 2011. The STS-134 imagery was part of a larger effort to demonstrate an emerging and reliable non-intrusive global thermal measurement capability and to complement a series of boundary layer transition flight experiments that were flown on the Shuttle. The STS-134 observations are believed to be the first time that the development and movement of a hypersonic boundary layer transition front has been witnessed in flight over the entire vehicle surface and in particular, at unprecedented spatial resolution. Additionally, benchmark surface temperature maps of the Orbiter lower surface collected over multiple flights and spanning a Mach range of 18 to 6 are now available and represent an opportunity for collaborative comparison with computational techniques focused on hypersonic transition and turbulence modeling. The synergy of the global temperature maps with the companion in-situ thermocouple measurements serve as an example of the effective leveraging of resources to achieve a common goal of advancing our understanding of the complex nature of high Mach number transition. It is shown that quantitative imaging can open the door to a multitude of national and international opportunities for partnership associated with flight-testing and subsequent validation of numerical simulation techniques. The quantitative imaging applications highlighted in this paper offer unique and complementary flight measurement alternatives and suggest collaborative instrumentation opportunities to advance the state of the art in transition prediction and maximize the return on investment in terms of developmental flight tests for future vehicle designs.

Horvath, Thomas J.↗
NASA NTRSDate not supplied

Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS): Robotically Assembled Sustainable Lunar Infrastructure

Introduction: The Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project at NASA Ames Research Center is developing autonomous infrastructure, instrumentation, and spacecraft assembly and manufacturing capabilities for next generation exploration and science missions, with a goal to change the cost scaling of these missions relative to mission size and duration. Using a building-block approach with a 'kit of parts' composed of ultra-light, high-performance mechanical metamaterials, simplified robots leverage the period environment to achieve high levels of autonomy and reliability for in-space and surface assembly of large-scale apertures, solar-arrays, towers, habitats, and other infrastructure. Robots and structure break down into a compact form factor for launch. By leveraging economies of scale and achieving high-packing ratios, ARMADAS technology can revolutionize possible space missions by breaking the tyranny of the launch shroud, decreasing development times, decreasing mission costs for transformative science capability, and providing a scalable and versatile space infrastructure strategy. Capabilities: To date, the ARMADAS project has demonstrated autonomous assembly of large numbers of structural modules into a meters-scale structure in an earth gravity environment. The mechanical performance is on par with conventional space structures, at a fraction of the cost. By using highly repeatable manufacturing processes (injection molding carbon fiber reinforced space-rated polymers), the structures are both cost effective and highly precise. The ARAMADAS system carefully designs parts for high-precision assembly–the simple and cost-effective robots build structures much larger and more precise than themselves. While maintaining structural efficiency, the ARMADAS system encompasses many functional module types, including for solar power, comm/power routing, etc., that will enable entire infrastructure systems to be engineered and autonomously assembled with modular parts. With well-defined interfaces, custom instrumentation modules can easily be added to fit many mission objectives. Lunar Infrastructure Vision: At the LSIC spring meeting, ARMADAS will present a vision for a general-purpose lunar construction kit capable of meeting a wide variety of lunar surface infrastructure needs (Figure 1). Investing in an ecosystem of reconfigurable, discretely repairable parts and robots enables systems than can expand their capability, reconfigure to meet emergency or unforeseen needs, self-repair and reduce spare-part needs. With a small set of parts (module types), a wide variety of infrastructure needs can be met. Footing modules will allow infrastructure construction at locations with no surface preparation. Footer, primary structure, and rail modules can create reconfigurable rail systems. These rail systems can be used to reduce cost-of-transport between frequently accessed sites, provide dust mitigation, and convey power and communications. High-performance structure modules combined with power-routing and solar modules can create tall towers for power and communication. Concepts for habitats and garages encompass a structure to support regolith cover for a pre-integrated module to an entirely ARMADAS system-based structure. This system can be leveraged by many in-situ resource utilization (ISRU) technologies to simplify processes and augment capabilities.

C. E. Gregg↗
DOE OSTI2022

Representing Socio‐Economic Uncertainty in Human System Models

Abstract Socio‐economic development pathways and their implications for the environment are highly uncertain, and energy transitions will involve complex interactions among sectors. Here, traditional Monte Carlo analysis is paired with scenario discovery techniques to provide a richer portrait of these complexities. Modeled uncertain input variables include costs of advanced energy technologies, energy efficiency trends, fossil fuel resource availability, elasticities of substitution for labor, capital, and energy across economic sectors, population growth, and labor and capital productivity. The sampled values are simulated through a multi‐sector, multi‐region, recursively dynamic model of the world economy to explore a range of possible future outcomes. We find that many patterns of energy and technology development are possible for various long‐term environmental pathways and that sectoral output for most sectors is little affected through 2050 by the long‐term temperature target, but with tight constraints on emissions, emission intensities must fall much more rapidly. Scenario discovery techniques are applied to the large uncertainty ensembles to explore if there are prevailing storylines behind outcomes of interest. An illustrative investigation focused on different levels of economic growth shows many combinations of pathways and no single storyline emerging for a given economic outcome. This method can be extended to other outcomes of interest, exploring the nature of scenarios with both tail and median outcomes. Sampling from a Monte Carlo generated ensemble provides a rich set of scenarios to investigate, and potentially aids in avoiding heuristic biases in less structured scenario approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

The Need for International Consensus and Acceptance of Free Released Material - 20177

World Nuclear Association (WNA) believes that the waste hierarchy is best implemented when a good compromise exists between disposal and reuse/recycling methods of valuable materials and waste generated by the nuclear industry. The rapid normalization of recycling in both domestic and industrial worlds strengthens WNA's position, as new facilities worldwide emerge providing treatment for clearance. As a foundation for reuse and recycling, the International Atomic Energy Agency (IAEA) provided international guidance on clearance (Safety Guide RSG 1.7) [1], defining associated threshold values approved by all member states. Nevertheless, despite this consensus, a lack of alignment of national regulations has occurred as countries have departed for this international guidance, leading to confusion, even between neighborhood countries. As a consequence, this discrepancy between national rules, despite industrial and technical international consensus based on radiological and environmental considerations appeared as a brake, weakening public acceptance as well as nuclear industry credibility. As a matter of fact, what is allowed in one side of a border may be forbidden on the other side. Conversely, an international consensus on clearance would promote: - Sustainability improvements, including preservation of natural and rare resources resulting from optimized recycling and reuse practices; - A broader acceptance of free released materials; - taking advantage of the available technologies worldwide in materials treatment aiming for clearance; - Increased sharing and use of methods, know-how and operators, leading to better efficiency, innovation, improvement as well as technical and financial mastery. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A review of active probing-based system identification techniques with applications in power systems

System identification is becoming a relevant research area for numerous applications in power grids due to the increasing complexity of the system. A paradigm shift in power system infrastructure driven by renewable energy resources, controllable loads, and new power electronics technologies have given rise to new challenges in power systems operation and control. This increased complexity of power systems and unavailability of physics-based models of most inverter-based resources requires that traditional modeling of power systems approaches be complemented by system identification-based black or grey box modeling techniques. In light of the importance of system identification and little attention paid to the applications of these techniques in transforming power systems, this paper provides a comprehensive review of active probing-based system identification methods in the context of power system applications. It reviews applications of both linear and nonlinear system identification with discussion on their potential and key takeaways. To motivate a further practical use in power systems, the paper provides an example of system identification, to develop a state space model of an unknown plant with step-by-step details. The paper highlights the advantages of using modern power electronics-based sources in the identification process and discusses the emerging research directions for future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

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↗
DOE OSTI2024

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↗
DOE OSTI2024

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 C 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↗
DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework 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. 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.

emissions↗
DOE OSTI2021

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗