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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SAF combustion and contrail formation research [Slides]

Sustainable aviation fuels (SAFs) offer an effective pathway to decarbonize the aviation sector, which accounts for about 5% of the global net effective radiative forcing, and is expected to double in the next two decades. A primary objective of the SAF GC Roadmap is to develop sustainable fuels that avoid “sooting, aerosols, and other contributors to vapor trail emissions." Another parts of this project is motivated by ongoing efforts to develop aromatic-free SAFs by using cycloalkanes to match seal swell characteristics of current fossil-based jet fuel (e.g. Jet A).

09 BIOMASS FUELS↗
DOE OSTI2026

Characterization of carbonaceous aerosols during TRACER-CAT

Absorbing aerosols (AA) have an important impact on the global radiation budget and cloud properties. The composition and properties of AA can vary substantially throughout the atmosphere, depending on the particle source and the influence of chemical aging. Uncertainties associated with the radiative effects of AA remain substantial. A key contributor to this uncertainty is understanding the extent to which coatings in general, and water uptake especially, alters absorption by AA particles and how this depends on particle composition. We deployed new and existing experimental tools during the Tracking Aerosol Convection Interactions Experiment (TRACER) campaign in Houston, TX as part of the Carbonaceous Aerosols Thrust (CAT) to provide detailed characterization of aerosol optical, chemical, and physical properties. Our TRACER-CAT measurements complemented and expanded on the planned TRACER instrumentation, allowing for more detailed characterization of aerosol properties of relevance to cloud development (a core focus of TRACER), such as the composition of particles that can act as cloud condensation nuclei, than would otherwise be available. Our measurements have allowed for assessment of the relationship(s) between AA optical properties (with a focus on absorption) and the chemical and physical characteristics (including the mixing state of black carbon (BC) containing particles). These field observations occurred in collaboration with Los Alamos National Laboratory in summer 2022 during the TRACER intensive operating period. The instrumentation we co-deployed provided for measurement of (i) multi-wavelength dry aerosol absorption, scattering, and extinction, (ii) the size-dependent composition and abundance of sub-micron aerosol, differentiating between those particles that do and do not contain BC, (iii) BC-specific concentrations and size distributions, (iv) particle size, and (v) the first field measurements at an ARM site of the influence of RH on multi-wavelength absorption by ambient AA. We have leveraged the natural variability of the atmosphere and of aerosol sources in the Houston region to (i) specifically disentangle contributions to light absorption from BC, absorbing organic carbon (brown carbon), and coatings on BC, (ii) characterize the mixing state of BC and assess the factors that give rise to compositional differences between BC-containing and BC-free aerosol, and (iii) establish how water uptake influences absorption and how any such effect depends on particle composition and BC mixing state. Overall, our study contributed to the mission of the Atmospheric System Research program in multiple ways. Through the deployment of complementary, advanced instrumentation for characterization of a wide range of aerosol properties our work helped to maximize the scientific impact of the TRACER campaign. Our work also allowed for development of new insights into the relationship(s) between aerosol composition, hygroscopicity, and the mixing state of BC with aerosol optical properties. Through this, our work has provided knowledge that can improve understanding and model representation of aerosol processes as they affect the Earth’s radiation budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Airborne Release Fractions from Surrogate Nuclear Waste Fires Containing Lanthanide Nitrates and Depleted Uranium Nitrate in 30% Tributyl Phosphate in Kerosene

Airborne contaminants from fires containing nuclear waste represent significant health hazards and shape the design and operation of nuclear facilities. Much of the data used to formulate DOE-HDBK-3010-94, “Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities,” from the U.S. Department of Energy, were taken over 40 years ago. The objectives of this study were to reproduce experiments from Pacific Northwest Laboratories conducted in June 1973 employing current aerosol measurement methods and instrumentation, develop an enhanced understanding of particulate formation and transport from fires containing nuclear waste, and provide modeling and experimental capabilities for updating current standards and practices in nuclear facilities. A special chamber was designed to conduct small fires containing 25 mL of flammable waste containing lutetium nitrate, ytterbium nitrate, or depleted uranium nitrate. Carbon soot aerosols showed aggregates of primary particles ranging from 20 to 60 nm in diameter. In scanning electron microscopy, ~200-nm spheroidal particles were also observed dispersed among the fractal aggregates. The 200-nm spherical particles were composed of metal phosphates. Airborne release fractions (ARFs) were characterized by leaching filter deposits and quantifying metal concentrations with mass spectrometry. The average mass-based ARF for 238 U experiments was 1.0 × 10 -3 with a standard deviation of 7.5 × 10 -4 . For the original experiments, DOE-HDBK-3010-94 states, “Uranium ARFs range from 2 × 10 -4 to 3 × 10 -3 , an uncertainty of approximately an order of magnitude.” Therefore, current measurements were consistent with DOE-HDBK-3010-94 values. ARF values for lutetium and ytterbium were approximately one to two orders of magnitude lower than 238 U. Furthermore, metal nitrate solubility may have varied with elemental composition and temperature, thereby affecting ARF values for uranium surrogates (Yb and Lu). In addition to ARF data, solution boiling temperatures and evaporation rates can also be deduced from experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Understanding aerosol properties in convective outflows during TRACER

Convective outflow boundaries commonly form across the southeastern U.S., often originating from storms initiated along sea-breeze fronts. As outflows spread, merge, and collide, they frequently trigger secondary convection in air masses already modified by primary storm outflow. This resulting air mass carries a distinctive aerosol population, which can influence the development of secondary convective cells. During the U.S. DOE TRACER field campaign in summer 2022, we investigated how outflows affect aerosol size, composition, and hygroscopicity across Greater Houston, Texas. Using a novel detection algorithm, we identified and verified 72 outflow boundaries from surface meteorological observations. In the relatively simple continental environment northwest of Houston, a common relationship emerged between CCN-inferred hygroscopicity (κ) and size-resolved aerosol concentrations. The κ of aerosols typically decreased in size ranges where aerosol concentrations increased following outflow passage and increased where concentrations decreased. In contrast, at the Atmospheric Radiation Measurement’s (ARM) fixed site in La Porte, Texas, the aerosol response depended on outflow direction, shaped by concentrated industrial and shipping activity to the north and south/southeast along the Houston Ship Channel. Concurrent size distribution and composition changes suggested case-specific variability in κ, with either reinforcing or offsetting effects. Outflows passing over industrial/shipping sectors often promoted less hygroscopic aerosol populations while cleaner residential outflows often favored more hygroscopic aerosol populations. These results highlight key aerosol changes following outflow passage, providing a foundation for improved understanding of aerosol-cloud interactions related to secondary convection initiation along or in the wake of outflow boundaries.

Thompson, Seth A. [Texas A & M Univ., College Stat↗
DOE OSTI2026

Improving the Confidence in Retrievals of Vertical Distributions of Cloud Condensation Nuclei Number Concentration from ARM Supported by Aircraft In Situ Observations

Accurate quantification of the vertical distribution of cloud condensation nuclei (CCN) number concentrations is critical for improving our understanding of aerosol–cloud interactions. Ground-based Raman lidars operated by the Atmospheric Radiation Measurement (ARM) program, together with surface CCN measurements, are used to retrieve vertically resolved CCN number concentrations (Retrieved Number concentration of CCN, RNCCN). These retrievals rely on several assumptions, including that aerosol composition is vertically homogeneous. To assess this assumption, we developed and tested a framework to infer the dominant aerosol classes/types at different altitudes. This was done by applying a k-Nearest-Neighbors (kNN) algorithm to lidar ratio and linear depolarization ratio measurements from Raman lidar. We evaluated the framework using aircraft aerosol and CCN measurements from the ARM Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) field campaign. The results show that RNCCN performance degrades as vertical aerosol complexity increases, i.e., RNCCN agrees with the aircraft CCN in vertically homogeneous conditions, but closure decreases in layered aerosol structures. To generalize beyond individual examples, we introduce a metric (heterogeneity index) that quantifies the vertical complexity by assessing the variation of inferred aerosol classes/types. Case-level statistics show a tendency for RNCCN and aircraft differences to increase with this metric. By detecting retrievals that are likely compromised by aerosol vertical heterogeneity, the proposed framework improves the interpretability and effective use of RNCCN used for long-term evaluation of models and aerosol–cloud interactions.

Tian, Jingjing↗
DOE OSTI2026

An Infrared Database of n/k Optical Constants for Calculating Aerosol Spectra for the PICARD Program

The objective of the PICARD Program is to develop fieldable sensing platforms for the rapid chemical identification of aerosol particles in plumes. Standoff detection involves interrogating the aerosol cloud from a distance using optical methods and probing the signal returned from direct backscattering from the aerosol particles or transmitted through the plume after reflection from a retroreflector or surface of opportunity (SOO). The identification of chemical species, however, in aerosols is complicated by their complex compositions and morphologies, chemical interferants, and non-uniform particle sizes. To advance standoff detection of aerosols, modelling the infrared transmittance, reflectance and scattering spectra of aerosolized liquid and solid chemical compounds is required, and then testing that model experimentally via laboratory and field experiments. To perform accurate modeling, the infrared optical constants (n/k), i.e., the complex refractive index, of the compounds of interest are required. Thus, PNNL was tasked to provide the optical constants for a set of analytes relevant to the PICARD program. This report describes the experimental techniques used to derive the optical constants of both liquid and solid compounds using established “gold-standard” protocols, how the experimental data are processed to produce the wavenumber dependent optical constant vectors, and how the data are used in the aerosol absorption spectra modeling.

complex refractive index↗
DOE OSTI2023

Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments

Abstract Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cloud microphysical structure analysis based on high-resolution insitu measurements

This study investigates the microphysical parameters and shapes of droplet size distributions (DSDs) along three aircraft traverses of developing convective clouds during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) Phase III 2015 at a sampling frequency of 25 Hz. The droplet number concentration (Nc, cm -3 ), and liquid water content (LWC, g m -3 ) present steep gradients within zones of a few tens of meters near the cloud edges and relatively gentle gradients in the strong updraft zones. Sometimes, the horizontal LWC distribution resembles a trapezoidal shape with steep LWC and Nc gradients near the cloud edges. The LWC maximums (LWC max ) are lower than the adiabatic LWCs, but the high adiabatic fractions in the cloud core indicate low dilution. High LWC/LWC max , largest droplets, and narrow and similarly shaped DSDs are found in the regions of high updrafts. Zones of low LWC/LWC max are found close to the cloud edges, where DSDs are highly diverse, containing both large and small droplets. Finally, we analyze the mixing diagrams. Significant in-phase turbulent fluctuations in LWC and N c were found. The effective radii change slightly across cloud updraft zones but decrease at the zone of low LWC/LWC max ratio close to cloud edges. The spectra of LWC and N c obey Kolmogorov -5/3 turbulence law. The radii of the correlation of LWC and N c in updraft zones are of several tens of meters. Filaments up to 120–175 m in size are also noticed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ARM Shortwave Spectral Radiometry Strategy Review Report

A meeting of experts in shortwave (SW) spectral measurements was held in February 2019 to discuss the current state of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrumentation and the potential scientific impact of these measurements. Instrument mentors and users reported significant progress in hyperspectral measurement quality, with good-quality data sets now possible at several field campaigns and fixed sites. Ongoing filter-based measurement improvements, including addition of the 1.6-micron channel to the multifilter rotating shadowband radiometer (MFRSR) and lunar tracking mode of the Cimel sun photometers, were also lauded as exciting developments to improve retrievals of aerosol radiative properties and size distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ARM Shortwave Spectral Radiometry Strategy Review Report

A meeting of experts in shortwave (SW) spectral measurements was held in February 2019 to discuss the current state of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrumentation and the potential scientific impact of these measurements. Instrument mentors and users reported significant progress in hyperspectral measurement quality, with good-quality data sets now possible at several field campaigns and fixed sites. Ongoing filter-based measurement improvements, including addition of the 1.6-micron channel to the multifilter rotating shadowband radiometer (MFRSR) and lunar tracking mode of the Cimel sun photometers, were also lauded as exciting developments to improve retrievals of aerosol radiative properties and size distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Developing a simulator-based satellite dataset for using machine learning techniques to derive aerosol-cloud-precipitation interactions in models and observations in a consistent framework

Aerosol-cloud-precipitation interactions (ACPI) remain a major uncertainty in understanding the Earth’s radiation budget and water cycle (including extremes). After decades of active research, various observationally based metrics have been developed to constrain ACPI in Earth System Models (ESMs), but direct comparison of model and data estimates can confound scientific understanding because limitations and uncertainties in sampling and retrieval procedures may combine with model deficiencies in process representations of ACPI to obstruct understanding. Furthermore, conventional ACPI metrics often vary from one regime to another, and the ACPI process representation in ESMs is also typically derived based on only a limited area/regime (even though the parameterization applies globally). To bridge the gap between models and data and to correctly describe ACPI in all regimes, we propose to construct a new CALIPSO-CloudSat merged dataset that is produced by the same algorithms used in satellite simulators in ESMs, and to use machine learning techniques to derive new ACPI metrics that can be accurately estimated by satellites and can provide meaningful constraints on cloud microphysical process representations in ESMs. The dataset will include measured and retrieved variables for aerosol, cloud, and precipitation from CALIPSO and CloudSat, and environmental variables from meteorological reanalysis. The data will be used to train a neural network to construct the ACPI metrics as a function of environmental conditions. The new ACPI formula will be used to constrain the ACPI in the Energy Exascale Earth System Model (E3SM), and to augment/reformulate the ACPI process representation in the E3SM to improve the simulation of the evolution of the atmosphere under different environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantification of Lanthanides in a Molten Salt Reactor Surrogate Off-Gas Stream Using Laser-Induced Breakdown Spectroscopy

To enable the deployment of molten salt reactor technology, the development of off-gas treatment systems and advanced monitoring tools capable of operating with high temperatures and radiation fields while delivering near real-time information is necessary. Here, we aim to fulfill this requirement and proposes laser-induced breakdown spectroscopy (LIBS) for monitoring molten salt aerosol streams. A sheath gas measuring method was developed to protect optical elements from aerosol particles and to ensure a relatively constant aerosol stream for measurement. An aqueous system was studied to demonstrate the utility of LIBS for monitoring possible fission products in an aerosol stream: Gd, Nd, and Sm up to 2000 parts per million (ppm). A calibration model was built using partial least squares (PLS) regression with five, six, and nine latent variables for Gd, Nd, and Sm, respectively. This calibration model successfully estimated the concentrations of three test samples, which were validated with inductively charged plasma optical emission spectroscopy measurements at a 99.9% confidence interval. To enhance these models, a genetic algorithm was used to filter the spectra before entering the PLS model, thereby limiting the spectral features being regressed to those with greater correlations to concentration. This allowed for the number of latent variables used in the PLS models to be reduced to four, three, and three for Gd, Nd, and Sm, respectively. Finally, the genetic algorithm-filtered PLS models were used to predict the concentrations of the aerosol stream on a real-time dataset and resulted in a 73%, 18%, and 25% improvement in root mean squared error of prediction compared to the original PLS models developed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Aerosol emissions from water-lean solvents for post-combustion CO 2 capture

Advanced water-lean solvents (WLS) for post-combustion CO 2 capture have been gaining interest due to their ability to reduce the parasitic penalty from energy needed for solvent regeneration. Commercial implementation of these novel CO 2 capture technologies hinges on successful control of amine emissions. RTI conducted a parametric study of fundamental and operational variables influence on overall amine aerosol and vapor emissions from our water-lean solvent eCO 2 Sol™ using our 6-kW equivalent bench-scale gas absorption system. The parametric testing used a simulated flue gas with 15 % CO 2 , 2.3–4.2 % H 2 O, and 0–6 ppm sulfite (SO 3 ) to examine the impact of the presence of aerosols to the capture performance and amine emissions from the system. The SO 3 reacts with water in the flue gas to create H 2 SO 4 , which forms liquid aerosol droplets and provide nucleation sites for growth of aerosols. Scanning Mobility Particle Sizer and Aerodynamic Particle Sizer instruments monitored the aerosol particle size distribution. Parametric testing results suggested that the presence of the aerosols in the flue gas could increase the overall amine emissions by 10X compared to the baseline emissions from WLS’s vapor pressure. Principal component analysis (PCA) and projection to latent squares (PLS) developed models to predict the aerosol-based amine emissions from process data. The predictive PLS model had a correlation coefficient (Q 2 ) of 0.92 and could predict the aerosol-based emissions from the NAS process with ±15 % accuracy (average absolute deviation, AAD). The PLS regression model also identified key variables affecting aerosol-based emissions from WLS.

42 ENGINEERING↗
DOE OSTI2022

The Global Atmosphere‐aerosol Model ICON‐A‐HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness

Abstract The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3‐HAM2.3 global atmosphere‐aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON‐A (icon‐aes‐1.3.00) global atmosphere model to yield the new ICON‐A‐HAM2.3 atmosphere‐aerosol model. The ICON‐A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub‐grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6‐HAM2.3 two‐moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON‐A‐HAM2.3 and ECHAM6.3‐HAM2.3, but the bias is larger in ICON‐A‐HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub‐tropical oceans. ICON‐A‐HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON‐A‐HAM2.3 compared to standard ICON‐A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON‐A‐HAM2.3 and in ECHAM6.3‐HAM2.3. In the extra‐tropics, a smaller multivariable bias is found for ICON‐A‐HAM2.3 than for ECHAM6.3‐HAM2.3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Near‐Cloud Aerosol Retrieval Using Machine Learning Techniques, and Implied Direct Radiative Effects

Abstract There is a lack of satellite‐based aerosol retrievals in the vicinity of low‐topped clouds, mainly because reflectance from aerosols is overwhelmed by three‐dimensional cloud radiative effects. To account for cloud radiative effects on reflectance observations, we develop a Convolutional Neural Network and retrieve aerosol optical depth (AOD) with 100–500 m horizontal resolution for all cloud‐free regions regardless of their distances to clouds. The retrieval uncertainty is 0.01 + 5%AOD, and the mean bias is approximately −2%. In an application to satellite observations, aerosol hygroscopic growth due to humidification near clouds enhances AOD by 100% in regions within 1 km of cloud edges. The humidification effect leads to an overall 55% increase in the clear‐sky aerosol direct radiative effect. Although this increase is based on a case study, it highlights the importance of aerosol retrievals in near‐cloud regions, and the need to incorporate the humidification effect in radiative forcing estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Aerosol Manufacturing Technology to Produce Low-Cobalt Li-ion Battery Cathodes

Although considerable progress has been made with battery materials over the last 10 years, the cathode remains a major performance-limiting material in Li-ion battery (LIB) technology. New materials and battery chemistries will overcome some of the remaining challenges, but cathode materials must also be manufactured at a lower cost and with a smaller environmental footprint using new processes that can also enable improved control over stoichiometry, morphology, and compositional homogeneity. Cabot, Argonne National Laboratory and SAFT research teams are combining their extensive expertise in particle synthesis, battery materials and cell design to develop a low-cost, flexible aerosol manufacturing technology for production of high-performance cathode active materials (CAM). This project will develop low-Co CAMs via Reactive Spray Technology (RST) and Flame Spray Pyrolysis (FSP) to reach performance targets of < 50 mg Cobalt/Wh.

25 ENERGY STORAGE↗
DOE OSTI2022

Development and Evaluation of E3SM‐MOSAIC: Spatial Distributions and Radiative Effects of Nitrate Aerosol

Abstract Nitrate aerosol plays an important role in affecting regional air quality as well as Earth's climate. However, it is not well represented or even neglected in many global climate models. In this study, we couple the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module with the four‐mode version of the Modal Aerosol Module (MAM4) in DOE's Energy Exascale Earth System Model version 2 (E3SMv2) to simulate nitrate aerosol and its radiative effects. We find that nitrate aerosol simulated by E3SMv2‐MAM4‐MOSAIC is sensitive to the treatment of gaseous HNO 3 transfer to/from interstitial particles related to accommodation coefficients of HNO 3 ( ) on dust and non‐dust particles. We compare three different treatments of HNO 3 transfer: (a) a treatment (MTC_SLOW) that uses a low in the mass transfer coefficient (MTC) calculation; (b) a dust‐weighted MTC treatment (MTC_WGT) that uses a high on non‐dust particles; and (c) a dust‐weighted MTC treatment that also splits coarse mode aerosols into the coarse dust and sea salt sub‐modes in MOSAIC (MTC_SPLC). MTC_WGT and MTC_SPLC increase the global annual mean (2005–2014) nitrate burden from 0.096 (MTC_SLOW) to 0.237 and 0.185 Tg N, respectively, mostly in the coarse mode. MTC_WGT and MTC_SPLC also produce stronger nitrate direct radiative forcing (−0.048 and −0.051 W m −2 , respectively) and indirect forcing (−0.33 and −0.35 W m −2 , respectively) than MTC_SLOW (−0.021 and −0.24 W m −2 ). MTC_WGT and MTC_SPLC improve nitrate surface concentrations over remote oceans based on limited observations and vertical profiles of nitrate concentrations against aircraft measurements below 400 hPa.

54 ENVIRONMENTAL SCIENCES↗