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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Towards Automated and High-Throughput Quantitative Sizing and Isotopic Analysis of Nanoparticles via Single Particle-ICP-TOF-MS

The work described herein assesses the ability to characterize gold nanoparticles (Au NPs) of 50 and 100 nm, as well as 60 nm silver shelled gold core nanospheres (Au/Ag NPs), for their mass, respective size, and isotopic composition in an automated and unattended fashion. Here, an innovative autosampler was employed to mix and transport the blanks, standards, and samples into a high-efficiency single particle (SP) introduction system for subsequent analysis by inductively coupled plasma–time of flight–mass spectrometry (ICP-TOF-MS). Optimized NP transport efficiency into the ICP-TOF-MS was determined to be >80%. This combination, SP-ICP-TOF-MS, allowed for high-throughput sample analysis. Specifically, 50 total samples (including blanks/standards) were analyzed over 8 h, to provide an accurate characterization of the NPs. This methodology was implemented over the course of 5 days to assess its long-term reproducibility. Impressively, the in-run and day-to-day variation of sample transport is assessed to be 3.54 and 9.52% relative standard deviation (%RSD), respectively. The determination of Au NP size and concentration was of <5% relative difference from the certified values over these time periods. Isotopic characterization of the 107 Ag/ 109 Ag particles (n = 132,630) over the course of the measurements was determined to be 1.0788 ± 0.0030 with high accuracy (0.23% relative difference) when compared to the multi-collector–ICP-MS determination.

36 MATERIALS SCIENCE↗
DOE OSTI2022

EVI-Equity

EVI-Equity (Electric Vehicle Infrastructure for Equity) is a $200k project, started around in June of 2021, with a funding from the Vehicle Technologies Office (VTO). The motivation was to create a new analytical capability that can enable us to quantify and investigate equitable access to and distribution of existing and future deployment of PEVs and EVSEs in neighborhoods, cities, states, and the nation. EVI-Equity is a bottom-up equity-focused analysis model, built upon individual (synthetic) households, aggregated by census block groups. It consists of four core components - community engagement, environmental profiling, household expenditures, and network design. Although there are some commonalities, EVI-Equity is not a vehicle choice model, charging simulation model, or transportation demand model. EVI-Equity is rather a cross-cutting analysis tool, dedicated for evaluating equitable EV adoption and EVSE deployment, encompassing and bridging a wide variety of related tools, models, and frameworks. Some of the results indicate the importance of used vehicle market for low-income households. The presentation also highlights similarities and variations as to preferred public charging locations. For example, regardless of household income, retail spots are the most preferred location for public charging, followed by curbside/street. However, the results also imply that the importance of workplace charging may vary with income - the lower the income, the less important. Environmental profiling results, with an example of ground-level ozone in Atlanta area, show that the contrast between the haves and the have nots of plug-in electric vehicles depends on location. The assessment of household expenditures illustrates the economic impact of home charging access on an individual household level - the lower the income, the greater the impact is. Lastly, Denver metro area and the state of South Dakota are used to showcase the impact of different network design of charging infrastructure, as well as alternative (vs. baseline/existing) electric vehicle adoption pattern.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2022

Upcycling Associated Natural Gas into Liquid Chemical Intermediates

This report assesses the opportunity to utilize associated natural gas (ANG) that is currently flared or vented by conversion to value-added chemicals. In cases where ANG production is not sufficient to justify on-site capture and added investments for transportation and storage, there may be commercial opportunities to perform conversion and value-added processing of ANG. This analysis focuses on CH 4 conversion to liquid intermediates, as opposed to gaseous product, due to the opportunity to transport large volumes of liquids, by truck or rail as opposed to pipeline. This report assesses market opportunities for four liquid intermediates: benzene, toluene, xylene, and formic acid.

03 NATURAL GAS↗
DOE OSTI2024

Sensitivity Analysis of Irradiated Fueled Experiments using the MOOSE Framework [Slides]

Modeling and simulation (M&S) methods are able to predict uncertainties in experimental parameters (e.g., power and fission density) during irradiation. A shortfall exists in predicting how sensitive some of the parameters will behave during the experimental process. Sensitivity and Uncertainty Quantification (SUQ) is critical in support of qualification and licensing reactor fuels. The application of a method to quantify the uncertainty in these experiments is critical to the prediction of their performance. In this work, we propose the use of a polynomial chaos expansion (PCE) method to quantify the sensitive parameters in these simulations and, in an extension, their experimental surrogates. We propose to perform M&S using PCE uncertainty quantification on a previously irradiated fueled experiment in order to provide a validation case for Griffin and expand its use as a verification and validation (V&V) tool for experiments with a neutronics component. Griffin is an advanced, deterministic neutronics analysis code built using the MOOSE (multiphysics object-oriented simulation environment) framework which can provide state-of-the-art neutronic analysis on M&S of experiments. We will use the stochastic tools module (STM) in MOOSE to provide PCE uncertainty quantification on the proposed experimental setup. Idaho National Laboratory (INL) does not yet have an in-house developed code with V&V approval for experiments performed on-site; this work would provide a necessary addition of support for experiments performed at INL. The Nuclear Regulatory Commission (NRC) has explicitly requested uncertainties in calculated values such as fuel power and burnup, and the development of this capability would benefit the relationship between INL and the NRC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Market Segmentation Analysis of Medium and Heavy Duty Trucks with a Fuel Cell Emphasis

The medium- and heavy-duty transportation sector is experiencing rapid changes in powertrain technology innovation with recent announcements of battery electric and fuel cell electric trucks being offered. However, the economics of these alternative powertrain vehicles are uncertain and difficult to compare directly. This analysis seeks to bridge the gap of techno-economic analyses for these alternative powertrain vehicles by comparing all of them within the same analytic framework. Specifically, this report evaluates the total cost of ownership (TCO) of six different truck powertrain technologies (diesel, diesel hybrid-electric, plug-in hybrid electric, compressed natural gas, battery electric, and fuel cell electric) for three different truck vocations (Class 8 long haul [750 mile range], Class 8 short haul [300 mile range], and Class 4 parcel delivery), for different Department of Energy technology statuses (2018, 2025, and Ultimate). The TCO framework includes direct costs (purchase price, fuel, operating and maintenance), indirect costs (dwell time costs due to refueling/recharging and payload opportunity costs from forgone revenue due to the truck being weight-limited), but excludes general operation costs (driver wages and benefits, insurance, tire replacements, permits, tolls) that are assumed to be the same across powertrains. The TCO was evaluated for four scenarios that reflect typical business operating conditions. The TCO analysis results highlight that each powertrain technology may have an economic advantage on a TCO basis in certain business operating conditions and depending on fuel price realized. For Class 8 long haul trucks when payload opportunity costs are not incurred, battery electric and fuel cell electric powertrains could be cost competitive with diesel if the 2025 targets are achieved and fuel prices are low. If payload opportunity costs are incurred, battery electric powertrains are not estimated to reach TCO parity with diesel even if Ultimate targets and low electricity prices are realized, indicating a need for significant vehicle lightweighting. In Class 8 short haul commercial applications when payload opportunity costs are not incurred, battery electric, fuel cell electric, and compressed natural gas vehicle powertrains have very competitive TCOs with diesel if the 2025 targets are achieved. In Class 8 short haul commercial applications when payload opportunity costs are incurred, the battery electric vehicle powertrains can achieve TCO parity with diesel only if the Ultimate battery prices are met ($80/kWh). In Class 4 parcel delivery truck operating scenarios where there are no dwell time costs incurred, the plug-in hybrid electric vehicle, battery electric vehicle, and fuel cell electric vehicle could be cost-competitive with diesel and compressed natural gas with current (2018) technology performance and costs. In general, the payload opportunity costs can be a significant driver to TCO for the Class 8 long and short haul commercial vehicle applications while the dwell time costs could be a major TCO cost driver for the Class 4 parcel delivery vehicle if the business scenario realizes those costs.

advanced powertrains↗
DOE OSTI2022

Recent Trends in Transport of Surface Carbonaceous Aerosols to the Upper-Troposphere-Lower-Stratosphere Linked to Expansion of the Asian Summer Monsoon Anticyclone

Using Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2) re-analyses, we have examined recent trends (2000–2019) in transport of surface carbonaceous aerosols (CAs), that is, organic carbon and black carbon, to the upper troposphere and lower stratosphere (UTLS) during the Asian summer monsoon (ASM). We find a significant increased concentration of UTLS CA, linked to a linear trend in an expansion of the Asian Summer Monsoon Anticyclone (ASMA). Over core monsoon latitudes (25°–35°N), the trends in UTLS CA are enabled by increased upward transport from surface sources via an intensified monsoon meridional circulation, with increased latent heating over the southern Tibetan Plateau and foothill regions, enhanced by feedback processes associated with radiative heating by UTLS CA. In the extra-tropics, increased UTLS CA stems primarily from an extended source of increased wildfire emissions over eastern Siberia and northern Asia, coincident with a large-scale anomalous anticyclone with enhanced surface warming and drying near (80°–120°E, 55°–70°N). Here, CAs are transported upward from the surface to the ULS, likely by increased pyro-convection associated with enhanced wildfires, and enter the tropical UTLS via increased equatorward transport on the eastern flanks of anomalous upper-level anticyclones, coupled to the expanded ASMA. Overall, the increasing UTLS CA trends associated with expansion of the ASMA are consistent with a hydrostatic expansion of a warming troposphere, reflected in a rise in the tropical tropopause and consequential dynamical adjustments of the ASM subtropical jetstream, modulating the climate of the greater ASM region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PORFLOW modeling of Vadose zone flow and transport for the E-area intermediate level vault

In support of the E-Area Performance Assessment, a two-dimensional model of water flow and radionuclide transport through the E-Area Intermediate Level Vault (ILV) and local vadose zone has been developed using the PORFLOWTM software. The purpose of the model is to calculate flux to the water table for radionuclides eluted from the ILV during its operational life, the period of institutional control, and times following site closure. Results of model calculations will be used by a three-dimensional PORFLOW model of transport through the aquifer to determine radionuclide concentrations at a hypothetical 100 meter well and at the site boundary where contaminated groundwater could be assessed by members of the public following site closure. While newly developed, the model structure closely follows that used in the 2008 PA while incorporating a refined computational mesh, updated material properties for the vadose zone soil and vault concrete, revised infiltration rates, and new solid-liquid distribution coefficients. The model also addresses degradation of concrete hydraulic properties by blending soil and concrete water retention curves over a 500 year period. That is, the hydraulic properties of ILV concrete start out as fresh concrete at the time of site closure and degrade to soil properties over a 500 year time period. This approach has not been used previously in E-Area PA’s. The model has been used to calculate water flow through the ILV vadose zone and, on a trial basis, transport of a limited number of radionuclides from the waste region inside the ILV to the water table. Figure ES-1 provides a view of the model and an example of water flow after the concrete has substantially degraded. Figure dimensions are in centimeters. The red area in the left hand side figure is the waste disposal region within the ILV. Colored bands in the figures indicate different soil and concrete regions. Figure ES-2 shows a calculation of flux to the water table (mol/yr) for U-234 and its one-year half-life decay chain (U-234 → Th-230 → Ra-226 → Pb-210). Pb-210 flux is too small to show on the same scale used for Th-230 and Ra-226 in Figure ES-2. The model has also been used to make a preliminary evaluation of the release of tritium from TPBAR disposal containers that will be place in the ILV. A separately calculated tritium release rate as a function of time was used as a source in the PORFLOW model. The TPBAR disposal schedule and tritium release rate differ from the values used in the 2008 PA. Results from these initial trial runs are compared to calculations made for the 2008 PA ILV analysis. In brief, a new PORFLOW model of flow and transport through the ILV vadose zone has been developed and tested. The model is ready to be used for PA calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Transporter annotations are holding up progress in metabolic modeling

Mechanistic, constraint-based models of microbial isolates or communities are a staple in the metabolic analysis toolbox, but predictions about microbe-microbe and microbe-environment interactions are only as good as the accuracy of transporter annotations. A number of hurdles stand in the way of comprehensive functional assignments for membrane transporters. These include general or non-specific substrate assignments, ambiguity in the localization, directionality and reversibility of a transporter, and the many-to-many mapping of substrates, transporters and genes. In this perspective, we summarize progress in both experimental and computational approaches used to determine the function of transporters and consider paths forward that integrate both. Investment in accurate, high-throughput functional characterization is needed to train the next-generation of predictive tools toward genome-scale metabolic network reconstructions that better predict phenotypes and interactions. More reliable predictions in this domain will benefit fields ranging from personalized medicine to metabolic engineering to microbial ecology.

Casey, John↗
DOE OSTI2020

Measurement of the Low-Energy Electron Inelastic Mean Free Path in Monolayer Graphene

Measuring the electron-transport properties of substrate-supported nanomaterials with the traditional two-point comparison method is difficult at electron energies below 50 eV, where core-level signals are too feeble to be detected against the strong secondary-electron background. Herein, a data-driven spectral analysis technique is used to study the low-energy electron-transport properties of substrate-supported target nanomaterials, while eliminating the influence of the substrate signal. Applying this technique, the electron-transport properties of the effective attenuation length and the inelastic mean free path (IMFP) can be determined with extremely high efficiency over the entire measured energy range of 6–600 eV. Further, these results show excellent agreement with other experimental and theoretical results. In this work, significant differences are observed between monolayer graphene and the bulk graphite IMFP, which illustrates the importance of the nanometer effect in the electron-transport properties of the material. Furthermore, this technique is readily applicable to any ultrathin material that can be transferred onto a polycrystalline gold substrate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Field-dependent carrier transport in implanted isolation region of GaN lateral power devices

Among GaN lateral power devices, with proper E-field management, the breakdown occurs in the device isolation region rather than the active region. In this paper, we investigate field-dependent carrier transport in the isolation structures. Isolation test structures with variations in buffer doping, un-intentionally doped (UID) GaN thickness, and implantation conditions were fabricated. Electrical characterization was performed over a wide range of voltage and temperature. With varying UID GaN thickness and buffer doping, the leakage current and breakdown characteristics remain the same for a specific implantation condition, indicating that the leakage conduction and breakdown are governed by the implanted GaN region. Analysis of the temperature-dependent I–V reveals that carrier transport in the implanted GaN can be well explained by hopping conduction, involving three distinctive regions of operation depending on the E-field. At low E-field, carrier transport is ohmic, consistent with variable range hopping, driven by thermal activation. At medium E-field, a field enhanced thermally activated hopping is observed, following σ ∼ σ(T)exp(E). At high E-field, activation-less hopping is visible, following σ ∼ exp(−1/E), which occurs above a critical E-field limited by localization length.

Sadek, Mansura (ORCID:0000000322588338)↗
DOE OSTI2026

Using Machine Learning to Understand Electric and Hybrid Vehicles Ownership in Burdened and Nonburdened Communities

Transitioning to electric and hybrid vehicles (EHVs) for all communities is a pivotal step toward sustainable transportation and environmental conservation. This paper aims to understand the adoption of EHVs, focusing on burdened communities (BCs) in the United States. The EHV ownership-based analysis combines two datasets—behavioral data from the Puget Sound Regional Travel Survey integrated with BCs (Justice40) data covering transportation insecurity, environmental burden, social vulnerability, health vulnerability, and climate and disaster risk burden. After creating this unique database, descriptive analysis and modeling are used to analyze the data and predict EHV ownership in the future. Specifically, we use a new method that combines particle swarm optimization (PSO) with a stacking model named PSO-Stacking, which incorporates heterogeneous base learners of machine learning and deep learning. PSO applies a customized objective function to select the optimal hyperparameters for heterogeneous learners within the stacking model, effectively addressing challenges such as multicollinearity, data imbalance, nonlinearity, and overfitting. The proposed solution covers more accurate results than standard benchmark models for EHV ownership in BCs and non-BCs. In addition, the results of the PSO-Stacking method are explained using the local interpretable model-agnostic explanations technique. Results show a negative correlation between the BCs indicators, that is, higher transportation insecurity associated with lower EHV ownership. Furthermore, BCs have higher future climate risk scores, diesel particulate matter levels, and PM2.5 in the air than non-BCs because of higher conventional vehicle ownership. These communities are at higher risk and can benefit from electrification, EV infrastructure, and EV policies to address environmental challenges.

Aslam, Zeeshan [ORNL]↗
DOE OSTI2025

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Analysis of near-field and far-field aerosol dispersion for microreactors

The current paper presents a simulation-based analysis of aerosol dispersion in the near-field and far-field of a generic, conceptual microreactor operating at pressures close to the ambient pressure; therefore, in the event of an accident that causes radionuclide leakage from the microreactor containment, the radionuclide particles are less likely to travel too far from the reactor, as opposed to conventional reactors. Accordingly, the presented work provides estimates of average and 95-percentile values of the relative effluent concentration. A parametric study is then performed to narrow down the parameters which affect the aerosol dispersion characteristics most significantly. Simulations were performed in the computer code ARCON96, and the parameters found to affect aerosol dispersion characteristics are the atmospheric stability class, and the distance between the release point and the receptor. It is recommended that the computer code RADTRAD be used to calculate actual dosage over distance, using the outputs from ARCON96 as inputs, along with reactor-specific core term inventories. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Overview of the Electrification of Transportation in Hawaii

This document is a summary of electric vehicle (EV) experiences in Hawaii. It is meant to be informative but does not present any new technical analysis except for the development of key lessons learned that could be applied in similar contexts. The electrification of transportation is essential for Hawaii's energy goal. An electrification of transportation strategy complements other energy policy goals, increases clean energy impacts, and provides customer value. By the end of 2020, there were over 12,000 EVs registered in Hawaii (about 1 percent of all cars). That number is expected to grow, based on the results from recent surveys and studies in Hawaii. Surveys pointed out the need for more charging stations, especially in places where people do business or park for long periods of the day. Participation in controlled charging programs should have attractive incentives since a majority of EV owners would not be willing to interrupt their EV charging for demand response. Various studies have confirmed the EV potential in Hawaii. For example, the JUMPSmart Maui demonstration project, a public-private partnership with Japan, helped to establish the EV charging station infrastructure in Maui and provided important information about charging behaviors. A critical backbone study commissioned by the utility recommended that 3,600 public chargers be installed by 2030 on the five islands, which confirms the need for infrastructure improvements expressed in earlier surveys. The process that emerged in Hawaii can be an example to other locations, which could heed the lessons from Hawaii's EV experiences: The importance of an overarching energy goal/objective based on a shared vision; planning and pilot projects; a strategic plan (roadmap) leveraging on initial experiences; evaluation of the effectiveness/success of actions; fine-tuning as needed; close regulatory oversight and stakeholder participation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Effects of a magnetic field on hot electron generation from laser-plasma instabilities

We performed two-dimensional simulations of turbulent laser-plasma instabilities in the presence and absence of external magnetic fields using the Laser Plasma Simulation Environment (LPSE) code. The results demonstrate that, in the presence of a magnetic field, the transition from ballistic to gyrating electron motion enhances the energy transfer from electron plasma waves to the electron population. Although stronger magnetic fields produce a larger population of hot electrons, these electrons tend to remain confined near the quarter-critical density, where the instabilities also localize, thereby reducing the potential for hot electron transport deeper into the target. Additionally, we present a scaling analysis that quantifies hot electron generation as a function of plasma electron temperature, density scale length, and applied magnetic field strength. These findings may have important applications for controlling hot electron flux and mitigating preheat in inertial confinement fusion targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Evidence for the 3D Radiative Effects of Boundary-Layer Clouds From Observations of Direct and Diffuse Surface Solar Fluxes

Numerical experiments have revealed the importance of horizontal transport of light in the presence of clouds (“3D effects”), with consequences for climate, weather, and solar resource availability predictions. Yet, analysis of 3D effects from observations remain sparse because of the difficulty to isolate the effect of horizontal transport in radiation measurements. In this study, we provide observational evidence for 3D effects based on the direct-diffuse partition of surface solar fluxes. It is compared to outputs from the ecRad radiative transfer scheme run on retrieved cloud profiles. Furthermore, the direct-beam calculation takes careful account of the field-of-view of the pyrheliometer to ensure consistency between observed and modeled direct fluxes. Only the solver that accounts for 3D effects is able to reproduce the observed mean direct-diffuse partition as a function of solar zenith angle and cloud cover, in particular at large solar zenith angles where cloud sides intercept most of the direct beam.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Quantifying the impacts of atmospheric rivers on the surface energy budget of the Arctic based on reanalysis

We present a comprehensive analysis of Arctic surface energy budget (SEB) components during atmospheric river (AR) events identified by integrated water vapor transport exceeding the monthly 85th-percentile climatological threshold in 3-hourly ERA5 reanalysis data from January 1980 to December 2019. Analysis of average anomalies in SEB components, net SEB, and the overall AR contribution to both the seasonal SEB components and net SEB climatology reveals clear seasonality and distinct land–sea–sea ice contrast patterns. Over the sea-ice-covered central Arctic Ocean, ARs significantly impact net SEB, inducing substantial surface warming in fall, winter, and spring. This warming is primarily driven by large anomalies in surface downward longwave radiation (LWD), which average 29–45 W m −2 during the cold seasons. In contrast, AR-related LWD anomalies are smaller in summer, averaging around 15 W m −2 , indicating a reduced impact during this season. Over sub-polar oceans, ARs have the most substantial positive impact on net SEB in cold seasons, mainly attributed to significant positive turbulent heat flux anomalies. AR-related turbulent heat anomalies reduce the upward turbulent flux, contributing up to −11 % relative to its seasonal climatology. In summer, ARs induce negative impacts on net SEB, primarily due to reduced shortwave radiation from increased cloud cover during AR events. Over continents, ARs generate smaller absolute impacts on net SEB because the large LWD anomalies are largely offset by corresponding increases in upward longwave radiation, particularly during cold seasons. Additionally, the seemingly large relative contributions of ARs to the net SEB over land primarily reflects the small magnitude of the climatological net SEB over continents. Greenland, especially western Greenland, exhibits significant downward longwave radiation anomalies associated with ARs, which drive large net SEB anomalies and contribute >54 % to mean SEB and induce amplified surface warming year-round. This holds significance for melt events, particularly during summer. Additionally, results of AR-related SEB impacts strongly depend on detection methods, as restrictive AR detection algorithms that emphasize extreme AR events, with large AR-related anomalies, do not necessarily indicate a large overall contribution to the SEB climatology due to the low occurrence frequency of these events. This study quantifies the role of ARs in the surface energy budget, contributing to our understanding of the Arctic warming and sea ice decline in ongoing Arctic amplification.

Arctic Sea ice change↗
DOE OSTI2023

Enabling a Sustainable Future: Zero-Emission Vehicles Cost Analysis to Inform Decarbonization Pathways

Despite being only 5% of vehicles on the road, medium- and heavy-duty vehicles (MHDVs) are the second largest contributor to transportation emissions (21%) and a major source of local air pollution disproportionally affecting disadvantaged communities. This talk summarizes a cost analysis for zero emissions vehicles (battery electric EVs and hydrogen fuel cell FCEVs) for all medium and heavy duty applications, ranging from large pick-up trucks, to delivery vans, buses, and heavy trucks. Results show that with continued improvements in vehicle and fuel technologies (in line with U.S. Department of Energy targets and vetted with industry), zero-emission vehicles (ZEVs) can reach total-cost-of-driving parity with conventional diesel vehicles by 2035 for all medium- and heavy-duty (MD/HD) vehicle classes without incentives. Assuming economics drives adoption, ZEV sales could reach 42% of all MD/HD trucks by 2030, reflecting lower combined vehicle purchase and operating costs (using real-world payback periods). Two technological solutions - battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) - are viable in multiple market segments, offering alternative pathways for decarbonization: a) BEVs tend to become cost-competitive for smaller trucks before 2030 and for short-haul (<500-mile) heavy trucks before 2035. b) Hydrogen FCEVs tend to become cost-competitive for long-haul (>500-mile) heavy trucks by 2035. Results are very sensitive to technology improvement trajectories, adoption decision-making, and uncertain assumptions about future freight demand, logistics, and vehicle use explored in multiple scenarios.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗