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At least 559 records · Page 31

Toward 2035: Forging a High-Ambition U.S. Climate Pathway

This analysis takes an integrated, innovative approach to develop plausible, high-ambition pathways through 2035 to inform the third U.S. NDC target setting. This approach combines: (1) an extensive consultation and engagement process with a broad set of federal and subnational stakeholders to build a robust U.S. policy platform; and (2) an open-source, field-leading integrated assessment model focused on the U.S. containing subnational details. The modeling tool assesses existing and possible new policies from both federal and subnational levels to assess the overall emissions reduction potential and the policy pathways to deliver the ambition needed for 2035 and leading on to 2050. In addition, we highlight how different actors can contribute to the needed transition in each sector and showcase successful implementation stories by various subnational actors.

54 ENVIRONMENTAL SCIENCES↗

In Search of Strategic Advantage: Understanding the Landscape of Technology Competition

In an era of seemingly ever-increasing global tensions, technology competition is often mentioned as a pathway for U.S. and allied success. The opening arguments are often very simple. “This is the most important struggle of the 21st century.” “We cannot afford to lose this competition.” “The United States must not fall behind in this race.” “We must be faster, more agile, more committed, more thoughtful than our competitors.” Competition around a particular technology is described as a once in a generational struggle with immense stakes. “This is a Sputnik moment” is a common analogy. The solutions proposed are fairly straightforward – more of everything. We should spend more money. We should build more widgets or more factories. We should innovate more. We should focus more. We should attract more talent. We should file more patents. We should produce more PhDs. If we do more of everything, we will have more technology than our opponents, they will see our technological advantage, they will not challenge us, and therefore we will win. If we fail to do these things, we will lose. To paraphrase Homer Simpson, in national security policy discussions technology competition has become the cause of, and solution to, all of life’s problems. And yet, beyond doing more across the board technology competition is not at all simple. First, it is a concept increasingly muddled together with other big issues such as innovation policy, national defense strategy, great power competition, allied cooperation, public-private partnerships, and a host of other issues. Certain policies, systems, coalitions, and so on may be excellent for tackling one challenge, but far less optional for others. Second, it is inherently dynamic, an action-reaction cycle between multiple players. A brilliant opening move can be squandered or successfully countered in subsequent moves. Third, there are limits to what you can do - limited time, limited financial resources, limited human capital, and limited knowledge of what lies ahead. One is forced to choose.

99 GENERAL AND MISCELLANEOUS↗

Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model

Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.

Artifical Intelligence↗

Why Terminology Matters for Successful Rollout of Carbon Dioxide Utilization Technologies

To realize their full sustainability potential, carbon dioxide utilization technologies (carbon capture and utilization/CCU) presently require policy support. Consequently, they require acceptance among a variety of stakeholders in industry, policy making, and in the public sphere alike. While CO 2 utilization is already a topic of discourse among these stakeholders, there is a lack of common terminology to describe such technologies. On the contrary: The present article shows that terminology in the field of CO 2 utilization technologies is currently used inconsistently, and that different designations such as CCU, CCUS, or CDR convey different meanings and contexts. These ambiguities may cause communication problems with regard to policy making, funding proposals, and especially in public discourse. In order to initiate and accompany a goal-oriented and knowledge-based debate on CO 2 utilization technologies in the future, actors in the field are asked to question their own choices of terminology and to assess its accuracy. Acronyms and technical abbreviations are the chief cause of potential misunderstandings, and so should be avoided whenever possible or else include a brief explanation. Consistent and precise use of terminology will facilitate transparent dialogue concerning CO 2 utilization in the future.

54 ENVIRONMENTAL SCIENCES↗

Future marine biofuels in the port of Seattle region

Marine transportation, a vital global sector, emits 3% of global annual greenhouse gas emissions, which are predicted to increase in the future. Marine biofuels derived from biomass or waste sources like wood residue, waste oil and municipal solid waste can be used for decarbonization. However, limited studies have explored if sufficient marine biofuels could be produced and supplied to major regional ports given feedstock, supply chain and technological constraints. We fill this gap by evaluating the feasibility of supplying marine biofuels to the Port of Seattle. The Regional Bio-Economy Model (RBEM) and the Freight and Fuel Transportation Optimization Tool (FTOT) are used to build scenarios for simulating marine biofuel production in the Port region. We harmonized technoeconomic assumptions for RBEM and FTOT, input FTOT feedstock utilization and routing outputs into RBEM, and modelled conversion, feedstock, and policy scenario variations in RBEM. In RBEM, overall biofuel production was constrained primarily by the biofuel cost, and then by feedstock availability. Providing policy incentives and reducing permitting time frames alleviated these constraints and spurred the buildout of a robust industry through industrial learning dynamics in the initial years. With these measures in place, the RBEM results show that 100% of fuel demand at the Port can be supplied by biofuels with policy incentives and suitable technoeconomic conditions, but the addition of transportation cost considerations using FTOT led to 27.8% of demand being able to be met by biofuels at reasonable fuel delivery cost.

09 BIOMASS FUELS↗

Optimal Operations Management of Mobility-on-Demand Systems

The emergence of the sharing economy in urban transportation networks has enabled new fast, convenient and accessible mobility services referred to as Mobilty-on-Demand systems (e.g., Uber, Lyft, DiDi). These platforms have flourished in the last decade around the globe and face many operational challenges in order to be competitive and provide good quality of service. A crucial step in the effective operation of these systems is to reduce customers' waiting time while properly selecting the optimal fleet size and pricing policy. In this paper, we jointly tackle three operational decisions: (i) fleet size, (ii) pricing, and (iii) rebalancing, in order to maximize the platform's profit or its customers' welfare. To accomplish this, we first devise an optimization framework which gives rise to a static policy. Then, we elaborate and propose dynamic policies that are more responsive to perturbations such as unexpected increases in demand. We test this framework in a simulation environment using three case studies and leveraging traffic flow and taxi data from Eastern Massachusetts, New York City, and Chicago. Our results show that solving the problem jointly could increase profits between 1% and up to 50%, depending on the benchmark. Moreover, we observe that the proposed fleet size yield utilization of the vehicles in the fleet is around 75% compared to private vehicle utilization of 5%.

Wollenstein-Betech, Salomón↗

Modeling Air Pollutant Emissions in the Provincial Level Road Transportation Sector in Korea: A Case Study of the Zero-Emission Vehicle Subsidy

South Korea has been suffering from high PM2.5 pollution. Previous studies have contributed to establishing PM2.5 mitigation policies but have not considered provincial features and sector-interactions. In that sense, the integrated assessment model (IAM) could complement the shortcomings of previous studies. IAM, capable of analyzing PM2.5 pollution levels at the provincial level in Korea, however, has not been developed yet. Hence, this study (i) expands on IAM which can represent provincial-level spatial resolution in Korea (GCAM-Korea) with air pollutant emissions modeling which focuses on the road transportation sector and (ii) examines the zero-emission vehicles (ZEVs) subsidy policy’s effects on PM2.5 mitigation using the expanded GCAM-Korea. Simulation results show that PM2.5 emissions decrease by 0.6–4.1% compared to the baseline, and the Seoul metropolitan area contributes 38–44% to the overall PM2.5 emission reductions. As the ZEVs subsidy is weighted towards the light-duty vehicle 4-wheels (LDV4W) sector, various spillover effects are found: ZEVs’ share rises intensively in the LDV4W sector leading to an increase in its service costs, and at the same time, driving bus service costs to become relatively cheaper. This, in turn, drives an increase in bus service demand and emissions discharge. Furthermore, this type of impact of the ZEVs subsidy policy does not reduce internal combustion engine vehicles (ICEVs) in freight trucks, although diesel freight trucks are a major contributor to PM2.5 emissions and also to NOx.

Roh, Minyoung↗

Light-duty Plug-in Electric Vehicles in China: Evolution, Competition, and Outlook

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025). From the demand side, small-sized sedans and compact sport utility vehicles with increased electric ranges are both popular for PEVs, and the electric range of over 60% of new battery electric vehicles in 2021 has been longer than 400 km. From the supply side, although foreign brands like Tesla are still competitive, the products by Chinese domestic automakers like BYD are becoming more attractive and cannibalizing the high-end market. However, the production capacity and cost of PEVs may be limited by the upstream of the supply chain – the battery manufacturing and supply chain inflation. In addition, it is also uncertain how much sales demand impacts will be caused by the potential global economic recession. The government firmly supports electrification and decarbonization of the vehicle industry by emphasizing the importance of the vehicle industry for promoting the greenhouse gas net zero by 2060. The dual-credit policy is regarded as the most critical regulation in a bid to restrain fuel consumption and promote PEV share. Still, the market is facing some technological obstacles, such as battery safety and driving range anxiety, before real prosperity. In addition, the Chinese electric vehicle market is seeing a trend toward the development of new technologies such as vehicle-to-X, autonomous driving, and connected vehicles.

Hao, Xu↗

A Decision Support Framework for Grid-Aware Electric Bus Charge Scheduling

While there are many advantages to electric public transit vehicles, they also pose new challenges for fleet operators. One key challenge is defining a charge scheduling policy that minimizes operating costs and power grid disruptions while maintaining schedule adherence. An uncoordinated policy could result in some buses running out of charge before completing their trip, while a grid agnostic policy might incur higher energy costs or cause an adverse impact on the grid’s distribution system. We present a grid aware decision-theoretic framework for electric bus charge scheduling that accounts for energy price, grid load, and bus status. The framework connects environmental models for traffic (SUMO) and the electric grid (GridLAB-D) to a planner, which evaluates bus charging decisions with regard to their long-term effect on grid reliability and cost. The framework has been evaluated on a simulation of Richland, WA’s bus and grid network, and compared to greedy methods.

EV, machine leaning, EV-Grid, Transportation, Grid↗

Climate of the Field: Snowmass 2021

How are formal policies put in place to create an inclusive, equitable, safe environment? How do these differ between different communities of practice (institutions, labs, collaborations, working groups)? What policies towards a more equitable community are working? For those that aren't working, what external support is needed in order to make them more effective? We present a discussion of the current climate of the field in high energy particle physics and astrophysics (HEPA), as well as current efforts toward making the community a more diverse, inclusive, and equitable environment. We also present issues facing both institutions and HEPA collaborations, with a set of interviews with a selection of HEPA collaboration DEI leaders. We encourage the HEPA community and the institutions & agencies that support it to think critically about the prioritization of people in HEPA over the coming decade, and what resources and policies need to be in place in order to protect and elevate minoritized populations within the HEPA community.

Hansen, Erin V.↗

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.

distribution system↗

Primal-Dual Differentiable Programming for Distribution System Critical Load Restoration: Preprint

Swift and reliable critical load restoration (CLR) can help make a distribution system resilient towards extreme events. To optimally achieve that, alongside practical concerns such as limiting online computational burden, some studies leverage model-free reinforcement learning (RL) to train control policies. Despite the advantages provided by RL algorithms, these approaches suffer from two issues: 1) the lack of a proper mechanism for constraint enforcement, and 2) poor sample efficiency. Therefore, in this paper, a primal-dual differentiable programming (PDDP) method is developed for guiding the training leading to a constraint-satisfying policy. Additionally, the model-based nature of the proposed method aims at improving sample efficiency. The experiment on a CLR problem demonstrates that PDDP can effectively train a control policy that both achieves desirable performance and satisfies required constraints.

differentiable programming↗

Heat pumps in the United States: Market potentials, challenges and opportunities, technology advances

The US heat pump market has been affected by the socioeconomic impacts of the COVID-19 pandemic. However, the Biden administration’s goal of net-zero greenhouse gas emissions by 2050 through electrification and clean energy technologies is accelerating the research, development, and deployment of heat pumps in the United States for improved energy performance, reduced greenhouse gas emissions, and wider adoption. The US heat pump market has experienced steady growth since 2010. In 2020, heat pumps surpassed gas furnace shipments for the first time, and the trend maintains through 2022. The current priority is to improve the affordability of energy and equitable access to heat pump technologies through cost reductions and further accelerate this trend. In addition, current R&D includes emphases on alternative refrigeration technology and lower–global warming potential refrigerants to reduce direct emissions. Heat pump market share is expected to grow as regulatory policies and financial incentives steer the building sector toward decarbonization. This paper reviews policies and market trends, discusses the challenges and opportunities in the current policy landscape, and reviews current research in the United States.

Malhotra, Mini↗

Blending Behavioral Science and Physics-Based Models Inform Equitable Decarbonization Pathways in the US Housing Stock: Preprint

A just energy transition is an imperative of the Biden-Harris Administration, emphasizing the equitable distribution of benefits through energy-efficient and decarbonizing household technologies. Understanding the factors that increase a household's willingness to adopt these technologies helps policymakers implement more targeted and effective approaches. Our research addresses this by blending 550,000 housing stock types and energy simulation data with a nationally representative survey on residential technology adoption and decision-making (n=10,000). We identify energy equity gaps across tenure and income, highlighting disparities in energy burdens and insecurity. Findings show that households with prior modification experience are more willing to renovate, suggesting that small-scale retrofit programs could foster greater willingness. Energy secure but burdened homeowners are least willing to modify, highlighting the need to consider energy bill perceptions in policy design. Nearly half of US households that are energy burdened also face energy insecurity, with a significant gap in assistance for low-income households. We emphasize the need to understand household perceptions to improve policy. This research underscores the importance of understanding household behaviors to improve policy effectiveness, offering actionable insights for policymakers to promote equitable housing upgrades and advance a decarbonized future.

behavioral science↗

Gender Mainstreaming in Nuclear Security: Strategies for Incorporating Gender Equality by Design in the IAEA Milestones Approach

Gender mainstreaming has emerged as a critical mechanism towards achieving gender equality in the development and implementation of laws, policies, and programs, including those related to national security. Gender mainstreaming is generally defined as the process of assessing the implications for women and men of any planned action, including legislation, policies, and programs, in all areas and at all levels, with the ultimate goal to achieve gender equality. Gender mainstreaming, which in essence can be thought of as “gender equality by design,” is an important element for building a robust nuclear security infrastructure. To date, however, gender mainstreaming has not been fully operationalized in the nuclear sector. For instance, the IAEA Milestones Approach, which provides important guidance to states seeking to develop nuclear power programs, has not yet incorporated or addressed gender considerations in its various phases or nuclear infrastructure issues, including those related to nuclear security. Therefore, this paper will argue that specifically for nuclear newcomer states, gender mainstreaming could serve as a powerful tool to integrate gender considerations into the design of laws, policies, programs, and entities necessary to successfully implement a nuclear power program. The objective of this study is twofold: first, to explore the concept of gender mainstreaming and its relevance to nuclear security, and second, to identify how gender can be incorporated into the IAEA Milestones Approach. The paper will emphasize the importance of developing guidance for the IAEA and nuclear newcomer states on how gender considerations could be incorporated throughout the development of a nuclear security program.

Siserman-Gray, Ioana-Cristina↗

Development of New Reactor Core Configuration for Power Uprate - Fuel Reload & Heat Processing Analyses, Core Design, System Safety Assessments, and Fuel Performance Analyses

With the passage of the Infrastructure Investment and Jobs Act in 2021 and the Inflation Reduction Act (IRA) in 2022, the United States stands at a critical juncture for the future of nuclear power. These landmark policies provide significant support for clean energy initiatives, positioning nuclear power as a key component of the nation’s strategy to reduce carbon emissions and achieve energy security. This growing emphasis on nuclear energy is driven by the need for reliable, low-carbon power sources as the country transitions away from fossil fuels. Federal policy, along with increasing state-level support, is encouraging investment in nuclear technology advancements to meet these demands. Building new nuclear power plants (NPPs), however, presents significant challenges due to high costs and long construction timelines. As a result, increasing the power output of existing NPPs through power uprates has emerged as a more feasible and cost-effective strategy. One key area of advancement is the development of accident-tolerant fuel (ATF), such as chromium-coated zirconium alloy cladding, which offers enhanced material performance, enabling power uprates in light water reactors (LWRs). Given the growing demand for nuclear energy fueled by federal policies and state initiatives, it is essential to evaluate the feasibility and benefits of significant power uprates in existing pressurized water reactors (PWRs) using advanced fuel technologies. The introduction of ATF concepts opens new opportunities for safely and economically achieving these power increases. Assessing whether these innovations can support substantial power uprates while maintaining operational safety is crucial to maximizing the potential of the nation’s existing nuclear infrastructure. This project aims to explore how power uprates can be achieved by boosting reactor thermal power output and optimizing reactor core design, while ensuring the safety and economic viability of NPPs. Specifically, it will focus on demonstrating the technical and economic feasibility of power uprates in a PWR using low 5-10% enrichment uranium (LEU+) high burnup (HBU) fuel combined with ATF concepts. In fiscal year 2024 (FY24), the research and development focus on building foundational models and conducting multi-physics performance and safety analyses to support the power uprate. The findings of the study would be shared through LWRS Seasonal Meetings, conferences and workshops with utility companies and researchers. These also serve as a basis for further study of fuel reloading optimization with ATF claddings.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Do Mandates Deliver Cost Reductions for Energy Storage?

In 2013, California implemented a mandate directing the state’s investor-owned utilities to procure 1325 MW of energy storage, to help integrate nondispatchable renewable sources of energy and assist the state in meeting its environmental goals. This paper evaluates this policy’s impact of both battery deployment, and cost, finding that as of 2019, the state was effective in spurring nearly 500 MWh of battery storage deployment over what would have been installed in absence of the policy. This additive deployment would have the effect of reducing global battery cell costs by roughly $1.00/ kWh, based on learning by doing. To support these findings, we utilize both a difference in differences estimation, and a synthetic control analysis, both of which allow us to compare battery deployment in California, to deployment in other states. To pair deployment to cost reduction, we use a learning curve analysis, which links battery shipments to cell and storage block costs. For policymakers, these results provide evidence to the effectiveness of mandates in promoting storage deployment and help explain how these policies can induce downstream effects.

Boff, Daniel S.↗

University Data Management Pilot Utilizing the Nuclear Research Data System

Background In 2022, the Office of Science and Technology Policy (OSTP) issued a memo that significantly reshaped the landscape of access to federally funded research. The memo mandated that all taxpayer-funded research be made available to the public without delay upon publication, without an embargo period, superseding the 2013 OSTP public access policy. This public access policy promotes transparency and the democratization of knowledge, ensuring that the fruits of scientific endeavors funded by federal agencies could be immediately accessed and built upon by scientists, educators, students, and the public at large. To implement the requirements of the OSTP guidance and DOE Public Access Plan, the Office of Nuclear Energy (NE) has implemented public access plan guidance and has identified several areas where better data management practices would further expand public access to important nuclear energy related scientific data, reports, and other technical products. Significant NE supported efforts are already underway for data management and public access to important nuclear energy related data.1 2 To address gaps in data management practices, and improve retention and accessibility of data, NE is actively exploring enhanced data management options utilizing its high-performance computing resources administered by its Nuclear Scientific User Facility Program. A newly piloted system, the Nuclear Research Data System (NRDS) acts as a portal for data collection and dissemination. Nuclear Energy University Program Research and Development Portfolio According to Web of Science, NEUP has produced 2,345 journal publication that have been cited more than 61,000 times3 and countless conference proceedings. These publications are publicly available through OSTI.gov and in the open literature. Additional scientific and technical products including project milestones that are not publications and NEUP project final reports are vetted through OSTI.gov and released once reviewed and approved by DOE. Since 2009, NEUP has awarded close to 1,000 different R&D projects in technical areas across the NE research programs. As of June 2023, 512 NEUP reports are publicly available on OSTI. The underlying data for projects is still held at universities, and data transfer, co-location, and dissemination has not occurred in a systematic way. NEUP data is currently accessible through myriad university-based data repositories, or through direct requests to PIs. The program identified this patchwork of repositories, or often lack of publicly available data, as a significant barrier to an organized, accessible, and comprehensive solution to sharing data with the larger nuclear energy community. Approach The goal of this pilot project is to establish a pathway to a consolidated long-term repository for NEUP project data. To accomplish this goal, the pilot strives to accomplish the following objectives: Establish data collection standards, including a standard set of required supplementary information to contextualize and support raw data files. Work with the HPC group collect and upload information and to modify the NRDS system, as needed, to support a standardized approach. Resolve potential barriers to successful roll out of an expanded data collection strategy, including modifying data management plan guidelines and establishing a document and data release process that accounts for potential intellectual property and/or export control concerns. Results Overall, the pilot was successful in collecting 8,982 raw and processes data files, 220 reports, 56 calibration files, and 5,931 other supplementary documents. Supplementary documents included experimental plans, methods, journal publications and conference proceedings, milestone reports, and final reports. Figure 2 shows the number of data sets and supplementary project information provided by each project. Projects has significantly different input, depending on experimental data produced and completeness of the datasets provided.

Data collection↗