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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Recommendations for Data-in-Transit Requirements for Securing DER Communications

With the adoption of Distributed Energy Resource (DER) interoperability standards, common communication protocols are now being deployed between power system operators and DER devices. In 2018, a revision to the US interconnection and interoperability standard, Institute of Electrical and Electronics Engineers (IEEE) Std. 1547, required DER equipment to have an IEEE 2030.5, IEEE 1815, or SunSpec Modbus communication exchange interface. This change supports the future transition to secure connection and exchange of information between the DER equipment and implementing parties, such as grid operators. Adoption of standardized communication protocols and associated information models is a critical step toward interoperability between power system operators and DER, such as photovoltaic (PV) and energy storage systems. However, security requirements for these standardized communication protocols are not comprehensive, resulting in non-standard and vendor-specific implementation that may leave DER equipment susceptible to cyberattacks. This paper examines the data-in-flight security requirements for standardized DER communication protocols, per IEEE 1547-2018 revision, as it relates to device authentication, key management, and encryption. The state of the art for these security features is also explored, addressing their impact on communication and performance of low-cost single board computers, which are typical of DER devices. In conclusion, a recommendation is provided to adopt a common set of communication requirements, which are intended to achieve interoperability and implement data security over DER network pathways, while ensuring reliable, secure, and real-time information delivery.

42 ENGINEERING↗
DOE OSTI2023

Discerning Deception: An Empirically-Driven Agent-Based Model of Expert Evaluation of Scientific Content

Both human subject experiments and computational, modeling and simulations have been used to study detection of deception. This work aims to combine these two methods by integrating empirically-derived information (from human subject experiments) into agent-based models to generate novel insights into the complex problems of detection of disinformation content. Computational experiments are used to simulate across multiple scenarios for evaluation and decision-making regarding the validity of potentially deceptive scientific documents. Factors influencing the human agent behaviors in the model were identified through a human subject experiment that was conducted to evaluate and characterize decision making related to disinformation discernment. Correlation and regression analyses were used to translate insights from the human subjects experiment to inform the parameterization of agent features and scenario development. Three scenarios were evaluated with the agent-based models to help evaluate the replicability of the simulations (validation analysis) and assess the influence of human agent and document features (sensitivity analyses). A replication of the human participant experiment demonstrated that the agent-based simulations compare favorably to empirical findings. The agent-based modeling was then used to conduct sensitivity analysis on the accuracy of deception detection as a function of document proportions and human agent features. Results indicate that precision values are adversely impacted when the proportion of deceptive documents is lower in the overall sample, whereas recall values are more sensitive to changes in human agent features. These findings indicate important nuances in accuracy evaluations that should be further considered (including consideration of potential alternate metrics) in future agent-based models of disinformation. Additional areas for future exploration include extension of simulations to consider other ways to align the agent-based model design with psychological theory and inclusion of agent-agent interactions, especially as it pertains to sharing of scientific information within an organizational context.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗
DOE OSTI2020

Direct Write of 3D Nanoscale Mesh Objects with Platinum Precursor via Focused Helium Ion Beam Induced Deposition

The next generation optical, electronic, biological, and sensing devices as well as platforms will inevitably extend their architecture into the 3rd dimension to enhance functionality. In focused ion beam induced deposition (FIBID), a helium gas field ion source can be used with an organometallic precursor gas to fabricate nanoscale structures in 3D with high-precision and smaller critical dimensions than focused electron beam induced deposition (FEBID), traditional liquid metal source FIBID, or other additive manufacturing technology. In this work, we report the effect of beam current, dwell time, and pixel pitch on the resultant segment and angle growth for nanoscale 3D mesh objects. We note subtle beam heating effects, which impact the segment angle and the feature size. Additionally, we investigate the competition of material deposition and sputtering during the 3D FIBID process, with helium ion microscopy experiments and Monte Carlo simulations. Our results show complex 3D mesh structures measuring ~300 nm in the largest dimension, with individual features as small as 16 nm at full width half maximum (FWHM). These assemblies can be completed in minutes, with the underlying fabrication technology compatible with existing lithographic techniques, suggesting a higher-throughput pathway to integrating FIBID with established nanofabrication techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CGOLS V: Disk-wide Stellar Feedback and Observational Implications of the Cholla Galactic Wind Model

Abstract We present the fifth simulation in the Cholla Galactic OutfLow Simulation (CGOLS) project—a set of isolated starburst galaxy simulations modeled over large scales (10 kpc) at uniformly high resolution (Δx≈ 5 pc). Supernova feedback in this simulation is implemented as a disk-wide distribution of clusters, and we assess the impact of this geometry on several features of the resulting outflow, including the radial profiles of various phases; mass, momentum, and energy outflow rates; covering fraction of cool gas; mock absorption-line spectra; and X-ray surface brightness. In general, we find that the outflow generated by this model is cooler, slower, and contains more mass in the cool phase than a more centrally concentrated outflow driven by a similar number of supernovae. In addition, the energy loading factors in the hot phase are an order of magnitude lower, indicating much larger losses due to radiative cooling in the outflow. However, coupling between the hot and cool phases is more efficient than in the nuclear burst case, with almost 50% of the total outflowing energy flux carried by the cool phase at a radial distance of 5 kpc. These physical differences have corresponding signatures in observable quantities: the covering fraction of cool gas is much larger, and there is greater evidence of absorption in low and intermediate ionization energy lines. Taken together, our simulations indicate that centrally concentrated starbursts are more effective at driving hot, low-density outflows that will expand far into the halo, while galaxy-wide bursts may be more effective at removing cool gas from the disk.

Astronomy & Astrophysics↗
DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Carbon Additive Manufacturing with a Near-Replica “Green-to-Brown” Transformation

Nanocomposites containing nanoscale materials offer exciting opportunities to encode nanoscale features into macroscale dimensions, which produces unprecedented impact in material design and application. However, conventional methods cannot process nanocomposites with a high particle loading, as well as nanocomposites with the ability to be tailored at multiple scales. A composite architected mesoscale process strategy that brings particle loading nanoscale materials combined with multiscale features including nanoscale manipulation, mesoscale architecture, and macroscale formation to create spatially programmed nanocomposites with high particle loading and multiscale tailorability is reported. The process features a low-shrinking (<10%) “green-to-brown” transformation, making a near-geometric replica of the 3D design to produce a “brown” part with full nanomaterials to allow further matrix infill. Here, this demonstration includes additively manufactured carbon nanocomposites containing carbon nanotubes (CNTs) and thermoset epoxy, leading to multiscale CNTs tailorability, performance improvement, and 3D complex geometry feasibility. The process can produce nanomaterial-assembled architectures with 3D geometry and multiscale features and can incorporate a wide range of matrix materials, such as polymers, metals, and ceramics, to fabricate nanocomposites for new device structures and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Application of Ionic Liquids for the Recycling and Recovery of Technologically Critical and Valuable Metals

Population growth has led to an increased demand for raw minerals and energy resources; however, their supply cannot easily be provided in the same proportions. Modern technologies contain materials that are becoming more finely intermixed because of the broadening palette of elements used, and this outcome creates certain limitations for recycling. The recovery and separation of individual elements, critical materials and valuable metals from complex systems requires complex energy-consuming solutions with many hazardous chemicals used. Significant pressure is brought to bear on the improvement of separation and recycling approaches by the need to balance sustainability, efficiency, and environmental impacts. Due to the increase in environmental consciousness in chemical research and industry, the challenge for a sustainable environment calls for clean procedures that avoid the use of harmful organic solvents. Ionic liquids, also known as molten salts and future solvents, are endowed with unique features that have already had a promising impact on cutting-edge science and technologies. This review aims to address the current challenges associated with the energy-efficient design, recovery, recycling, and separation of valuable metals employing ionic liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Artificial dynamical effects in quantum field theory

In Newtonian mechanics, studying a system in a non-Galilean reference frame can lead to inertial pseudoforces appearing, such as the centrifugal force that seems to arise in dynamics analysed in a rotating frame. Likewise, artificial effects may arise in relativistic quantum field theory (QFT) if a system is studied in a framework that violates Poincaré invariance. Here, we highlight how such issues complicate the traditional canonical quantization of QFTs and can lead to a subjective description of natural phenomena. By contrast, the treatment of the same problem using light-front quantization is free from spurious pseudoeffects because Poincaré invariance is effectively preserved for all practical intents and purposes. We illustrate these statements using several examples: the Gerasimov-Drell-Hearn (GDH) relation, a fundamental feature of QFT; the absence of any measurable impact of Lorentz contraction in high-energy collisions; and the fictitious character of vacuum fluctuation contributions to the cosmological constant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Voltage waveform tailoring for high aspect ratio plasma etching of SiO 2 using Ar/CF 4 /O 2 mixtures: Consequences of ion and electron distributions on etch profiles

The quality of high aspect ratio (HAR) features etched into dielectrics for microelectronics fabrication using halogen containing low temperature plasmas strongly depends on the energy and angular distribution of the incident ions (IEAD) onto the wafer, as well as potentially that of the electrons (EEAD). Positive ions, accelerated to high energies by the sheath electric field, have narrow angular spreads and can penetrate deeply into HAR features. Electrons typically arrive at the wafer with nearly thermal energy and isotropic angular distributions and so do not directly penetrate deeply into features. These differences can lead to positive charging of the insides of the features that can slow etching rates and produce geometric defects such as twisting. In this work, we computationally investigated the plasma etching of HAR features into SiO 2 using tailored voltage waveforms in a geometrically asymmetric capacitively coupled plasma sustained in an Ar/CF 4 /O 2 mixture at 40 mTorr. The tailored waveform consisted of a sinusoidal wave and its higher harmonics with a fundamental frequency of 1 MHz. We found that some degree of control of the IEADs and EEADs is possible by adjusting the phase of higher harmonics φ through the resulting generation of electrical asymmetry and electric field reversal. However, the IEADs and EEADs cannot easily be separately controlled. The control of IEADs and EEADs is inherently linked. The highest quality feature was obtained with a phase angle φ = 0° as this value generated the largest (most negative) DC self-bias and largest electric field reversal for accelerating electrons into the feature. That said, the consequences of voltage waveform tailoring (VWT) on etched features are dominated by the change in the IEADs. Although VWT does produce EEADs with higher energy and narrower angular spread, the effect of these electrons on the feature compared to thermal electrons is not large. Finally, this smaller impact of VWT produced EEADs is attributed to thermal electrons being accelerated into the feature by electric fields produced by the positive in-feature charging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Synthesis of the Candidate Topological Compound Ni 3 Pb 2

Spin-orbit coupling enables the realization of topologically nontrivial ground states. As spin-orbit coupling increases with increasing atomic number, compounds featuring heavy elements, such as lead, offer a pathway toward creating new topologically nontrivial materials. Here, by employing a high-pressure flux synthesis method, we synthesized single crystals of Ni 3 Pb 2 , the first structurally characterized bulk binary phase in the Ni-Pb system. Combining experimental and theoretical techniques, we examined structure and bonding in Ni 3 Pb 2 , revealing the impact of chemical substitutions on electronic structure features of importance for controlling topological behavior. From these results, we determined that Ni 3 Pb 2 completes a series of structurally related transition-metal-heavy main group intermetallic materials that exhibit diverse electronic structures, opening a platform for synthetically tunable topologically nontrivial materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Regulators’ Financial Toolbox: Designing Low- and Moderate- Income (LMI) Community Solar Compensation Programs

On February 9, 2022, as part of the NARUC Winter Policy Summit, five NARUC Staff Subcommittees (Energy Resources and the Environment, Rate Design, Electricity, Electric Reliability and Resilience, and Consumers and the Public Interest) co-hosted two sessions on community solar. The first panel was Community Solar I: Benefits for Low- and Moderate-Income Consumers, featuring opening remarks from moderator Hon. Eric Blank, Chairman of the Colorado Public Utilities Commission, and presentations from Richard Caperton, Vice President, Policy and Market Development, Arcadia, on behalf of the Coalition for Community Solar Access (CCSA); Chris Nichols, Senior Program Director, Groundswell; and Ted Trabue, Managing Director, DC Sustainable Energy Utility. See presentations and recordings. The second panel, titled What is Community Solar 2: Cost Impacts to Participants and Non-Participants, featured opening remarks from moderator Jamie Barber, Director of the Energy Efficiency and Renewable Energy Unit at the Georgia Public Service Commission, and presentations from Dr. Gabriel Chan, Associate Professor, Humphrey School of Public Affairs, University of Minnesota; Matthew McDonnell, Managing Director, Strategen Consulting; and Katie Chiles Ottenweller, Southeast Director, Vote Solar. See presentations and recordings.

14 SOLAR ENERGY↗
DOE OSTI2023

Performance assessment for climate intervention (PACI): preliminary application to a stratospheric aerosol injection scenario

As the prospect of exceeding global temperature targets set forth in the Paris Agreement becomes more likely, methods of climate intervention are increasingly being explored. With this increased interest there is a need for an assessment process to understand the range of impacts across different scenarios against a set of performance goals in order to support policy decisions. The methodology and tools developed for Performance Assessment (PA) for nuclear waste repositories shares many similarities with the needs and requirements for a framework for climate intervention. Using PA, we outline and test an evaluation framework for climate intervention, called Performance Assessment for Climate Intervention (PACI) with a focus on Stratospheric Aerosol Injection (SAI). We define a set of key technical components for the example PACI framework which include identifying performance goals, the extent of the system, and identifying which features, events, and processes are relevant and impactful to calculating model output for the system given the performance goals. Having identified a set of performance goals, the performance of the system, including uncertainty, can then be evaluated against these goals. Using the Geoengineering Large Ensemble (GLENS) scenario, we develop a set of performance goals for monthly temperature, precipitation, drought index, soil water, solar flux, and surface runoff. The assessment assumes that targets may be framed in the context of risk-risk via a risk ratio, or the ratio of the risk of exceeding the performance goal for the SAI scenario against the risk of exceeding the performance goal for the emissions scenario. From regional responses, across multiple climate variables, it is then possible to assess which pathway carries lower risk relative to the goals. The assessment is not comprehensive but rather a demonstration of the evaluation of an SAI scenario. Future work is needed to develop a more complete assessment that would provide additional simulations to cover parametric and aleatory uncertainty and enable a deeper understanding of impacts, informed scenario selection, and allow further refinements to the approach.

climate intervention↗
DOE OSTI2026

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential R410A heat pump, and the performance was compared with two baseline VRC algorithms. The results are: (1) The proposed algorithm outperforms for the case with subcooling temperature less than 1 °C. (2) The proposed algorithm achieves a tested mean absolute percentage error (MAPE) of 4.23%, and improves the overall accuracy for cooling conditions by approximately 60%, compared with the two baseline algorithms. (3) The proposed algorithm uses two fewer features and improves the accuracy for undercharge cooling conditions by 68.0%, compared with baseline algorithm 2. These improvements enhance prediction accuracy and prevent overfitting, providing a more reliable refrigerant charge level prediction and helping improve the heat pump energy efficiency.

Liang, Chenjiyu↗
DOE OSTI2021

Advanced Nanocarbons for Enhanced Performance and Durability of Platinum Catalysts in Proton Exchange Membrane Fuel Cells

Insufficient stability of current carbon supported Pt and Pt alloy catalysts is a significant barrier for proton-exchange membrane fuel cells (PEMFCs). As a primary degradation cause to trigger Pt nanoparticle migration, dissolution, and aggregation, carbon corrosion remains a significant challenge. Compared with enhancing Pt and PtM alloy particle stability, improving support stability is rather challenging due to carbon's thermodynamic instability under fuel cell operation. In recent years, significant efforts have been made to develop highly durable carbon-based supports concerning innovative nanostructure design and synthesis along with mechanistic understanding. Here, this review critically discusses recent progress in developing carbon-based materials for Pt catalysts and provides synthesis–structure–performance correlations to elucidate underlying stability enhancement mechanisms. The mechanisms and impacts of carbon support degradation on Pt catalyst performance are first discussed. The general strategies are summarized to tailor the carbon structures and strengthen the metal–support interactions, followed by discussions on how these designs lead to enhanced support stability. Based on current experimental and theoretical studies, the critical features of carbon supports are analyzed concerning their impacts on the performance and durability of Pt catalysts in fuel cells. Finally, the perspectives are shared on future directions to develop advanced carbon materials with favorable morphologies and nanostructures to increase Pt utilization, strengthen metal-support interactions, facilitate mass/charge transfer, and enhance corrosion resistance.

25 ENERGY STORAGE↗
DOE OSTI2025

Understanding the impacts of inorganic species in woody biomass for preprocessing and pyrolysis–A review

Woody biomass represents an abundant resource for sustainable biofuels, biochemicals, and bioproducts. Technologies for converting woody biomass have been established for decades, and research consistently highlights the critical role of inorganic species and ash plays in feedstock handling and conversion processes, including equipment plugging, corrosion, and catalyst deactivation. A thorough understanding of the variability, transport behavior, and downstream impact of inorganic species in woody biomass is essential for defining feedstock quality specifications and developing effective management strategies for conversion processes. This review compiles critical information in five main sections: 1) inorganic species concentration in woody biomass, based on anatomical fractions and their sources of variability; 2) technique features for quantifying inorganic elemental chemical analysis; 3) impacts of inorganic species on biomass preprocessing; 4) impacts of inorganic species on pyrolysis, and 5) mitigation strategies. Additionally, this review explores future challenges and opportunities in addressing the impacts of inorganic species on biomass quality. These insights aim to support the sustainable development of the biomass-to-bioenergy pipeline and ensure high-quality lignocellulosic feedstocks for efficient downstream conversions. The findings offer valuable guidance to policy makers, industry stakeholders, and researchers in developing effective strategies for managing inorganic species in woody biomass and fostering the sustainable processes for lignocellulosic biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2023

Characterization of the aerosol vertical distributions and their impacts on warm clouds based on multi-year ARM observations

Aerosol vertical distribution plays a crucial role in cloud development and thus precipitation since both aerosol indirect and semi-direct effects significantly depend on the relative position of aerosol layer in reference to cloud, but its precise influence on cloud remains unclear. In this study, we integrated multi-year Raman Lidar measurements of aerosol vertical profiles from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) facility with available Value-Added Products of cloud features to characterize aerosol vertical distributions and their impacts on warm clouds over the continental and marine ARM atmospheric observatories, i.e., Southern Great Plains (SGP) and Eastern North Atlantic (ENA). A unimodal seasonal distribution of aerosol optical depths (AODs) with a peak in summer is found at upper boundary layer over SGP, while a bimodal distribution is observed at ENA for the AODs at lower levels with a major winter-spring maximum. The diurnal mean of upper-level AOD at SGP shows a maximum in the early evening. According to the relative positions of aerosol layers to clouds we further identify three primary types of aerosol vertical distribution, including Random, Decreasing, and Bottom. It is found that the impacts of aerosols on cloud may or may not vary with aerosol vertical distribution depending on environmental conditions, as reflected by the wide variations of the relations between AOD and cloud properties. For example, as AOD increases, the liquid water paths (LWPs) tend to be reduced at SGP but enhanced at ENA. The relations of cloud droplet effective radius with AOD largely depend on aerosol vertical distributions, particularly showing positive values in the Random type under low-LWP condition (<50gm -2 ). In conclusion, the distinct features of aerosol-cloud interactions in relation to aerosol vertical distribution are likely attributed to the continental-marine contrast in thermodynamic environments and aerosol conditions between SGP and ENA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerosol characteristics at the Southern Great Plains site during the HI-SCALE campaign

Abstract. Large uncertainties exist in global climate model predictions of radiative forcing due to insufficient understanding and simplified numerical representation of cloud formation and cloud–aerosol interactions. The Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in north-central Oklahoma to provide a better understanding of land–atmosphere interactions, aerosol and cloud properties, and the influence of aerosol and land–atmosphere interactions on cloud formation. The HI-SCALE campaign consisted of two intensive observational periods (IOPs) (April–May and August–September, 2016), during which coincident measurements were conducted both on the G-1 aircraft platform and at the SGP ground site. In this study we focus on the observations at the SGP ground site. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Ionicon proton-transfer-reaction mass spectrometer (PTR-MS) were deployed, characterizing chemistry of non-refractory aerosol and trace gases, respectively. Contributions from various aerosol sources, including biogenic and biomass burning emissions, were retrieved using factor analysis of the AMS data. In general, the organic aerosols at the SGP site was highly oxidized, with oxygenated organic aerosol (OOA) identified as the dominant factor for both the spring and summer IOP though more aged in spring. Cases of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) and biomass burning events were further investigated to understand additional sources of organic aerosol. Unlike other regions largely impacted by IEPOX chemistry, the IEPOX SOA at SGP was more highly oxygenated, likely due to the relatively weak local emissions of isoprene. Biogenic emissions appear to largely control the formation of organic aerosol (OA) during the HI-SCALE campaign. Potential HOM (highly oxygenated molecule) chemistry likely contributes to the highly oxygenated feature of aerosols at the SGP site, with impacts on new particle formation and global climate.

54 ENVIRONMENTAL SCIENCES↗