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

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Regional Emissions Analysis of Light-Duty Battery Electric Vehicles

Light-duty battery electric vehicles (BEVs) can reduce both greenhouse gas (GHG) and criteria air pollutant (CAPs) emissions, when compared to gasoline vehicles. However, research has found that while today’s BEVs typically reduce GHGs, they can increase certain CAPs, though with significant regional variability based on the electric grid mix. In addition, the environmental performance of electric and gasoline vehicles is not static, as key factors driving emissions have undergone significant changes recently and are expected to continue to evolve. In this study, we perform a cradle-to-grave life cycle analysis using state-level generation mix and vehicle operation emission data. We generated state-level emission factors using a projection from 2020 to 2050 for three light-duty vehicle types. We found that BEVs currently provide GHG benefits in nearly every state, with the median state’s benefit being between approximately 50% to 60% lower than gasoline counterparts. However, gasoline vehicles currently have lower total NOx, urban NOx, total PM 2.5 , and urban PM 2.5 in 33%; 15%; 70%; and 10% of states, respectively. BEV emissions will decrease in 2050 due to a cleaner grid, but the relative benefits when compared to gasoline vehicles do not change significantly, as gasoline vehicles are also improving over this time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Canadian Oil Sands Extraction and Upgrading: A Synthesis of the Data on Energy Consumption, CO 2 Emissions, and Supply Costs

As Canadian crude bitumen production from oil sands has increased in recent decades, the nation’s oil and gas industry has become a significant contributor to national greenhouse gas emissions. Canada has developed carbon emission reduction targets to meet its Nationally Determined Contributions and Mid-Century Strategy goals. A detailed profile of energy consumption pathways in the oil sands industry is necessary to identify potential areas of improvement and to monitor progress toward meeting emissions reduction targets. Much of the existing literature for oil sands modeling provides input assumptions with different technological boundaries. For a set of oil sands extraction and upgrading technologies, this study first reviews the literature and then quantifies energy input requirements, CO 2 emissions, and operating costs for a set of consistent technological boundaries and energy units. Summary results refer to requirements and costs at the production facility, excluding transportation and blending costs. An energy system diagram of oil sands production that matches these boundaries is provided, which can be used by integrated assessment models, oil sands companies, and government ministries to evaluate the present and future energy consumption and emissions pathways of the oil sands industry.

02 PETROLEUM↗
DOE OSTI2024

Predictive Modeling of NOx Emissions from Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends Using Flame Imaging and Machine Learning

This research paper explores the use of machine learning to relate images of flame structure and luminosity to measured NOx emissions. Images of reactions produced by 16 aero-engine derived injectors for a ground-based turbine operated on a range of fuel compositions, air pressure drops, preheat temperatures and adiabatic flame temperatures were captured and postprocessed. The experimental investigations were conducted under atmospheric conditions, capturing CO, NO and NOx emissions data and OH* chemiluminescence images from 27 test conditions. The injector geometry and test conditions were based on a statistically designed test plan. These results were first analyzed using the traditional analysis approach of analysis of variance (ANOVA). The statistically based test plan yielded 432 data points, leading to a correlation for NOx emissions as a function of injector geometry, test conditions and imaging responses, with 70.2% accuracy. As an alternative approach to predicting emissions using imaging diagnostics as well as injector geometry and test conditions, a random forest machine learning algorithm was also applied to the data and was able to achieve an accuracy of 82.6%. This study offers insights into the factors influencing emissions in ground-based turbines while emphasizing the potential of machine learning algorithms in constructing predictive models for complex systems.

08 HYDROGEN↗
DOE OSTI2019

Energy Consumption and CO 2 Emissions in Ironmaking and Development of a Novel Flash Technology

The issues of energy consumption and CO 2 emissions of major ironmaking processes, including several new technologies, are assessed. These two issues are interconnected in that the production and use of fuels to generate energy add to the total amount of CO 2 emissions and the efforts to sequester or convert CO 2 require energy. The amounts of emissions and energy consumption in alternate ironmaking processes are compared with those for the blast furnace, currently the dominant ironmaking process. Although more than 90% of iron production is currently through the blast furnace, intense efforts are devoted to developing alternative technologies. Recent developments in alternate ironmaking processes, which are largely driven by the needs to decrease CO 2 emissions and energy consumption, are discussed in this article. This discussion will include the description of the recently developed novel flash ironmaking technology. This technology bypasses the cokemaking and pelletization/sintering steps, which are pollution prone and energy intensive, by using iron ore concentrate. This transformational technology renders large energy saving and decreased CO 2 emissions compared with the blast furnace process. Economic analysis indicated that this new technology, when operated using natural gas, would be economically feasible. As a related topic, we will also discuss different methods for computing process energy and total energy requirements in ironmaking.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Förster Resonance Energy Transfer and Enhanced Emission in Cs 4 PbBr 6 Nanocrystals Encapsulated in Silicon Nano-Sheets for Perovskite Light Emitting Diode Applications

Encapsulating Cs 4 PbBr 6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs 4 PbBr 6 ellipsoidal nanocrystals and pseudo-spherical quantum dots in silicon nano-sheets and their enhanced photoluminescence (PL). For a sample with low concentrations of quantum dots in silicon nano-sheets, the emission from Cs 4 PbBr 6 pseudo-spherical quantum dots is quenched and is dominated with Pb 2+ ion/silicene emission, which is very stable during the whole measurement period. For a high concentration of Cs 4 PbBr 6 ellipsoidal nanocrystals in silicon nano-sheets, we have observed Förster resonance energy transfer with up to 87% efficiency through the oscillation of two PL peaks when UV excitation switches between on and off, using recorded video and PL lifetime measurements. In an area of a non-uniform sample containing both ellipsoidal nanocrystals and pseudo-spherical quantum dots, where Pb 2+ ion/silicene emissions, broadband emissions from quantum dots, and bandgap edge emissions (515 nm) appear, the 515 nm peak intensity increases five times over 30 min of UV excitation, probably due to a photon recycling effect. This irradiated sample has been stable for one year of ambient storage. Cs 4 PbBr 6 quantum dots encapsulated in silicon nano-sheets can lead to applications of halide perovskite light emitting diodes (PeLEDs) and integration with traditional semiconductor materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hubble Space Telescope UV and Hα Measurements of the Accretion Excess Emission from the Young Giant Planet PDS 70 b

Recent discoveries of young exoplanets within their natal disks offer exciting opportunities to study ongoing planet formation. In particular, a planet’s mass accretion rate can be constrained by observing the accretion-induced excess emission. So far, planetary accretion is only probed by the Hα line, which is then converted to a total accretion luminosity using correlations derived for stars. However, the majority of the accretion luminosity is expected to emerge from hydrogen continuum emission, and is best measured in the ultraviolet (UV). In this paper, we present HST/WFC3/UVIS F336W (UV) and F656N (Hα) high-contrast imaging observations of PDS 70. Applying a suite of novel observational techniques, we detect the planet PDS 70 b with signal-to-noise ratios of 5.3 and 7.8 in the F336W and F656N bands, respectively. This is the first time that an exoplanet has been directly imaged in the UV. Our observed Hα flux of PDS 70 b is higher by 3.5σ than the most recent published result. However, the light curve retrieved from our observations does not support greater than 30% variability in the planet’s Hα emission in six epochs over a five month timescale. We estimate a mass accretion rate of 1.4±0.2×10{sup −8}M{sub Jup} yr{sup −1}. Hα accounts for 36% of the total accretion luminosity. Such a high proportion of energy released in line emission suggests efficient production of Hα emission in planetary accretion, and motivates using the Hα band for searches of accreting planets. These results demonstrate HST/WFC3/UVIS’s excellent high-contrast imaging performance and highlight its potential for planet formation studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Characterizing the X-Ray Emission of Intermediate-mass Pre-main-sequence Stars

We use X-ray and infrared observations to study the properties of three classes of young stars in the Carina Nebula: intermediate-mass (2–5 M {sub ⊙}) pre-main-sequence stars (IMPS; i.e., intermediate-mass T Tauri stars), late-B and A stars on the zero-age main sequence (AB), and lower-mass T Tauri stars (TTS). We divide our sources among these three subclassifications and further identify disk-bearing young stellar objects versus diskless sources with no detectable infrared (IR) excess emission using IR (1–8 μm) spectral energy distribution modeling. We then perform X-ray spectral fitting to determine the hydrogen-absorbing column density (N {sub H}), absorption-corrected X-ray luminosity (L {sub X}), and coronal plasma temperature (kT) for each source. We find that the X-ray spectra of both IMPS and TTS are characterized by similar kT and N {sub H}, and on average L {sub X}/L {sub bol} ~ 4 × 10{sup -4}. IMPS are systematically more luminous in X-rays (by ~0.3 dex) than all other subclassifications, with median L {sub X} = 2.5 × 10{sup 31} erg s{sup -1}, while AB stars of similar masses have X-ray emission consistent with TTS companions. These lines of evidence converge on a magnetocoronal flaring source for IMPS X-ray emission, a scaled-up version of the TTS emission mechanism. IMPS therefore provide powerful probes of isochronal ages for the first ~10 Myr in the evolution of a massive stellar population, because their intrinsic, coronal X-ray emission decays rapidly after they commence evolving along radiative tracks. We suggest that the most luminous (in both X-rays and IR) IMPS could be used to place empirical constraints on the location of the intermediate-mass stellar birth line.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Emissions minimization on road networks via Generic Second Order Models

In this paper we consider the problem of estimating emissions due to vehicular traffic on complex networks, and minimizing their effect by regulating traffic at junctions. For the traffic evolution, we consider a Generic Second Order Model, which encompasses the majority of two-equations (i.e., second-order) models available in the literature, and extend it to road networks with merge and diverge junctions. The dynamics on the whole network is determined by selecting a solution to the Riemann Problems at junctions, i.e., the Cauchy problems with constant initial data on each incident road. The latter are solved by assuming the maximization of the flow and assigning a traffic distribution coefficient for outgoing roads of diverges, and a priority rule for incoming roads of merges. A general emission model is considered and its parameters are tuned to the $ {\mathrm{NO_{x}}} $ emission rate. The minimization of emissions is then formulated in terms of the traffic distribution and priority parameters, taking into account travel times. A comparison is provided between roundabouts with optimized parameters and traffic lights, which correspond to time-varying traffic priorities. Our approach can be adapted to manage traffic in complex networks in order to reduce emissions while keeping travel time at acceptable levels.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

An Open-Source Decarbonization Analytics Framework: Designing for Low-Carbon Emission Districts and Communities: Preprint

This paper introduces an open-source analytics framework designed to assist in creating low or net-zero carbon buildings and urban districts. Integrated within URBANopt, an open-source platform for energy analysis in districts and communities, this framework equips researchers, architects, engineers, and other stakeholders with tools to evaluate the carbon footprint implications of their design choices. The framework enables the analysis of various scenarios, incorporating both historical and future emission factors, and can span across different climate zones, each with distinct grid and emissions characteristics. The results showcase the framework's capability to evaluate the impact of design upgrades and control strategies on carbon emissions in districts and communities. An illustrative analysis using a hypothetical district in Denver, Colorado, shows reduced emissions from energy efficiency upgrades and control strategies, highlighting the sensitivity in their effects on emissions and energy use.

buildings energy efficiency↗
DOE OSTI2024

Comparison of Silicon Decarbonization Methods to Reduce Process Emissions and Energy Consumption

The demand for silicon is rising due to its use in solar cells, electronics, and alloying as part of the green transition. However, these products require silicon metal (metallurgical grade silicon, >98% Si) as their main raw material before undergoing further chemical refining, usually via gas phase in methods such as the Siemens process. Silicon metal is currently produced in a submerged arc furnace via carbothermic reduction of quartz, which results in 10-12 tCO2/tSi. More than 40% of these emissions are process emissions, meaning they do not include contributions from electricity generation or transport. This talk will discuss promising methods to reduce or eliminate these process emissions. These include the use of biocarbon and carbon capture, aluminothermic reduction, electrochemical reduction with molten salts, and use of hydrogen in a modified Siemens process. Biocarbon and carbon capture is a straightforward method to reduce the net carbon emissions of the process, but long-term sustainable production of high-quality charcoal is a challenge. Aluminothermic reduction makes good use of aluminum byproducts such as dross but is perhaps limited in its applications to aluminum-silicon alloy products. Electrochemical reduction is promising as a method of producing high purity Si from quartz, without further need for the Siemens process, but is still in early stages of research and slow processing times are a concern. Finally, the use of hydrogen in a modified Siemens process would also result in a high purity Si product from quartz, however the process has considerable logistical challenges with corrosive and unstable gases at high temperatures. This talk will further expand on the potential merits and challenges of each method, while comparing their potential to reduce emissions and/or energy consumption while meeting global demand.

decarbonization↗
DOE OSTI2025

BRE‐X Emissions Database for End‐of‐Life Scenarios of Selective Building Construction Materials to Enable Circular Economy in Construction

In the United States, construction and demolition debris predominately end up in landfills with minimal end‐of‐life Re‐X (recover, recycle, reuse, etc.) scenarios, resulting in large environmental impacts and lost opportunities for material recovery. Except for concrete and metals, which seem to have a few well‐defined end‐of‐life pathways, there seems to be a lack of well‐documented end‐of‐life scenarios for other construction materials, let alone their emissions data. Hence, there is a need for documented end‐of‐life Re‐X scenarios and end‐of‐life data of more building materials to motivate widespread use of Re‐X strategies in building design. This paper outlines the efforts of the National Renewable Energy Laboratory, Carbon Leadership Forum, Building Transparency, and Skidmore, Owings & Merrill to (a) create an open‐access BRE‐X (Building Re‐X) end‐of‐life emissions database consisting of greenhouse gas emissions data associated with various end‐of‐life scenarios for a select list of high‐impact building construction materials, and (b) integrate the BRE‐X end‐of‐life emissions database with CAD/BIM/LCA tools for evaluating various end‐of‐life scenarios. The paper also presents a few existing life cycle inventory databases that contain sparse amounts of end‐of‐life data for a few construction materials and their limitations in terms of scaling and data consolidation. Finally, a sample of how the collected data can be ingested into whole‐building LCA tools using open data formats and a public access link to the BRE‐X end‐of‐life emissions database is also included.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Summertime methane and carbon dioxide emission rates and associated variables from a national‐scale survey of 146 reservoirs in the United States

Reservoirs are globally important sources of greenhouse gases, but the magnitude of their emissions is highly uncertain. Here, we present data for 146 reservoirs from two surveys of reservoir methane and carbon dioxide emissions, one at the regional scale in the midwestern United States and one at the national scale in the United States, plus data from two hand‐picked sites in Washington and Puerto Rico. At all reservoirs, ebullitive and diffusive emissions and basic physicochemistry were measured at 15–55 locations during one 22 to 64‐h period during the summers of 2016–2023, with four reservoirs revisited a second time. Contemporaneous water chemistry measurements were made at one or two locations in each reservoir. The dataset consists of two geospatial files and seven CSV files containing greenhouse gas emissions, water chemistry, morphology, and other relevant data. To date, these data comprise the largest multi‐reservoir emissions dataset assembled using consistent measurement methods.

Beaulieu, Jake J. [US Environmental Protection Age↗
DOE OSTI2023

Effects of Water Table Fluctuation on Greenhouse Gas Emissions from Wetland Soils in the Peruvian Amazon

Amazonian swamp forests remove large amounts of carbon dioxide (CO 2 ) but produce methane (CH 4 ). Both are important greenhouse gases (GHG). Drought and cultivation cut the CH 4 emissions but may release CO 2 . Varying oxygen content in nitrogen-rich soil produces nitrous oxide (N 2 O), which is the third most important GHG. Despite the potentially tremendous changes, GHG emissions from wetland soils under different land uses and environmental conditions have rarely been compared in the Amazon. We measured environmental characteristics, and CO 2 , CH 4 and N 2 O emissions from the soil surface with manual opaque chambers in three sites near Iquitos, Peru from September 2019 to March 2020: a pristine peat swamp forest, a young forest and a slash-and-burn manioc field. The manioc field showed moderate soil respiration and N 2 O emission. The peat swamp forests under slight water table drawdown emitted large amounts of CO 2 and CH 4 . A heavy post-drought shower created a hot moment of N 2 O in the pristine swamp forest, likely produced by nitrifiers. All in all, even small changes in soil moisture can create hot moments of GHG emissions from Amazonian wetland soils, and should therefore be carefully monitored.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Electrifying High-Efficiency Future Communities: Impact on Energy, Emissions, and Grid

To combat climate change and meet decarbonization goals, the building sector is improving energy efficiency and electrifying end uses to reduce carbon emissions from fossil fuels. All-electric buildings are becoming a trend among new constructions, introducing opportunities for decarbonization but also technical challenges and research gaps. For instance, further investigation is needed to understand how the adoption of energy efficiency measures (EEMs) and distributed energy resources (DERs) in all-electric communities would affect energy consumption, carbon emissions, and grid planning. This paper presents a case study of a mixed-use, all-electric community located in Denver, Colorado. We use URBANopt TM , a physics-based urban energy modeling platform to model the community and then evaluate the impact of EEMs and DERs (i.e., photovoltaics [PV], electric vehicles [EVs], and batteries) on the community's energy usage, carbon emissions, and peak demand. The results show that adding EEMs and PV led to both energy consumption and carbon emissions reductions across all building types. However, we saw fairly limited impact of EEMs and PV on buildings' peak demand in our case. Additionally, due to overnight EV charging activities and higher grid carbon intensity at night, the carbon emissions in multifamily buildings have a noticeable increase compared to scenarios without vehicles. Finally, the addition of batteries helped reduce peak demand by 11%-29%. The modeling workflow and evaluation methods can be applied to similar communities to evaluate their performance and the effect of integrating EEMs and DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Carbon emission responsive building control: A case study with an all-electric residential community in a cold climate

In the United States, buildings account for 35% of total energy-related carbon dioxide emissions, making them important contributors to decarbonization. Carbon intensities in the power grid are time-varying and can fluctuate significantly within hours, so shifting building loads in response to the carbon intensities can reduce a building’s operational carbon emissions. This paper presents a rule-based carbon responsive control framework that controls the setpoints of thermostatically controlled loads responding to the grid’s carbon emission signals in real time. Based on this framework, four controllers are proposed with different combinations of carbon accounting methods and control rules. To evaluate their performance, we performed simulation studies using models of a 27-home, all-electric, net zero energy residential community located in Basalt, Colorado, United States. The carbon intensity data of four future years from the Cambium data set are adopted to account for the evolving resource mix in the power grid. Various performance metrics, including energy consumption, carbon emission, energy cost, and thermal discomfort, were used to evaluate the performance of the controllers. Sensitivity analysis was also conducted to determine how the control thresholds and intervals affect the controllers’ performance. Simulation results indicate that the carbon responsive controllers can reduce the homes’ annual carbon emissions by 6.0% to 20.5%. However, the energy consumption increased by 0.9% to 6.7%, except in one scenario where it decreased by 2.2%. Compared to the baseline, the change in energy cost was between –2.9% and 3.4%, and thermal discomfort was also maintained within an acceptable range. The little impact on energy cost and thermal discomfort indicates there are no potential roadblocks for customer acceptance when rolling out the controllers in utility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Transportation in net-zero emissions futures: Insights from the EMF-37 model intercomparison study

Transportation is currently the largest source of U.S. anthropogenic CO 2 emissions, at about a third of the total. Achieving net-zero emissions by mid-century will require substantial reductions in transportation emissions across passenger and freight travel. Here we leverage a model intercomparison study to explore the role of transportation in scenarios achieving net-zero economy-wide CO 2 emissions by 2050. We find the transport sector is poised to play the most significant role in reducing demand-side emissions, mostly driven by technology substitution, as modeling results suggest a limited role for mode shifting and for reduced use of personal car travel in the U.S. Among various technology solutions, models show agreement that passenger on-road vehicles will largely transition to electric vehicles (EVs), while solutions to decarbonize heavier travel modes are more diverse and include greater use of liquid biofuels and hydrogen. Research should continue to investigate the evolution of on-road electrification, the role of biofuels and hydrogen across heavier travel modes, and the role of mode shifting and travel behavior change to support personal transportation decarbonization at national and regional scales to temper the rapid growth in clean fuel and electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Spatiotemporal flame propagations, combustion and solid particle emissions from lean and stoichiometric gasoline direct injection engine operation

Increased particle number and mass emissions in gasoline direct injection (GDI) engines should require to investigate in-cylinder flame and combustion characteristics associated with primary source of particle emissions. In this article, in-cylinder spatiotemporal flame luminosity is quantitatively characterized to features combustion process and solid particle emissions from a GDI engine operating in two lean and one stoichiometric modes. Low- and high-steady state operating points were used to compare combustion strategies on flame development and emission characteristics. A fiber-optic sensor composed of eight measurement channels detected the flame front and the direction of the flame propagation in the combustion chamber. Solid particle emissions in the exhaust were measured using an engine exhaust particle sizer and a micro soot sensor. Results of the experiments showed that two lean combustion modes by injection strategies resulted in distinct combustion and flame development. Lean combustion modes generated high diffusion flame by burning stratified rich-mixture. Although the lean cases resulted in strong diffusion flames, the lean-homogeneous produced similar particle size distributions with the stoichiometric mode with high ash particles. Piston pool fires on the piston surface in the lean-stratified mode induced a large accumulation mode with high particle mass concentrations.

42 ENGINEERING↗