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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data and code for Daily and Multi-Day Extreme Rainfall Analysis Under Future Climates Using Stochastic Storm Transposition and NEX-GDDP-CMIP6 Over CONUS

This data package provides inputs, codes, and outputs for a comprehensive analysis of projected changes in extreme precipitation across 10 regions of the continental United States, using 34 downscaled Earth System Models (ESMs) from the NASA Earth Exchange Global Daily Downscaled Projections, Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6) dataset. These models are part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), a coordinated climate modeling framework widely used to assess climate change impacts. The analysis applies a stochastic storm transposition method to quantify changes in extreme rainfall under two Shared Socioeconomic Pathway (SSP) climate scenarios—SSP2-4.5 (moderate emissions) and SSP5-8.5 (high emissions)—compared to historical conditions (1995–2014 vs. 2081–2100). The dataset includes rainfall depth estimates for extreme events with return periods from 2 to 500 years across multiple storm durations (1, 3, and 5 days) for each of the 10 U.S. regions. Weighted ensemble statistics are derived from individual ESM performance against historical precipitation patterns, enabling robust uncertainty quantification through both sign-based and permutation-test-based model agreement assessments. Key analyses address: (1) relative changes in extreme precipitation for each climate scenario, (2) differences between SSP scenarios (SSP5-8.5 vs. SSP2-4.5), (3) contrasts between rare and frequent events, and (4) variations between multi-day and daily storm durations. The workflow produces ensemble statistics—median, 5th, 25th, 75th, and 95th percentiles—along with model agreement metrics that identify regions and event types with robust climate change signals. The dataset includes: processed rainfall depth outputs (netCDF format) from the RainyDay Python package, ESM weights from historical performance evaluation using DayMet observations, ensemble statistics across all storm dimensions, and figures summarizing key findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Rules of Use Report Engineering evaluations of nuclear material storage containers against the packaging requirements at TA-55

A set of obligations in the yearly storage container surveillance program, ensures that a retrospective approach is applied with loaded containers in inventory to confirm compliance with all “users” to ensure nuclear material storage container requirements are being followed. Validation that packaged containers are properly used, within a specific set of container types prescribed “bounding conditions of use,” is based on meeting requirements as identified in operating procedures associated with TA55-DOP-091, TA-55 Nuclear Material Packaging, and PA-RD-01022, Nuclear Material Packaging Requirements. The surveillance plan obligation requires the application of local area nuclear material accountability software or (LANMAS) to produce queries. The data queries are used to assess attributes of containers in storage these investigations are conducted on a bi-annual basis. This rules of use (ROU) compliance process ensures proper usage of storage containers as containment systems and therefore provides effective worker protection. It is structured as a supporting effort by implementing aspects of PA-AP-01207, Nuclear Material Container Safety Management at TA-55.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Engineering evaluations of nuclear material storage containers against the packaging requirements at TA-55 (FY22 Rules of Use Report)

A set of obligations in the yearly storage container surveillance program, ensures that a retrospective approach is applied with loaded containers in inventory to confirm compliance with all “users” to ensure nuclear material storage container requirements are being followed. Validation that packaged containers are properly used, within a specific set of container types prescribed “bounding conditions of use,” is based on meeting requirements as identified in operating procedures associated with TA55-DOP-091, TA-55 Nuclear Material Packaging, and PA-RD-01022, Nuclear Material Packaging Requirements. The surveillance plan obligation requires the application of local area nuclear material accountability software or (LANMAS) to produce queries. The data queries are used to assess attributes of containers in storage these investigations are conducted on a bi-annual basis. This rules of use (ROU) compliance process ensures proper usage of storage containers as containment systems and therefore provides effective worker protection. It is structured as a supporting effort by implementing aspects of PA-AP-01207, Nuclear Material Container Safety Management at TA-55.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An assessment of existing barriers to market adoption of thermal energy storage in buildings based on interviews with stakeholders

The United States administration recently established a goal of reducing greenhouse gas emissions by half below 2005 levels by 2030 and becoming a carbon-neutral economy by 2050. The transition to renewable energy sources may be significantly aided by energy storage. Energy storage could smooth the delivery of variable or intermittent renewable energy sources such as wind, hydro, and sun by storing excess renewable energy when it’s available and delivering it back when renewable energy production is low. Thermal energy storage (TES) is a way that stores thermal energy by heating or cooling a storage medium, which is then used for space heating and cooling, industrial processes, or power generation purposes later. This TES operation could lessen the demand for electricity in both the winter's and the summer's peak hours of electricity. While there are various studies that focus on the advancements and successes of TES technology, less attention is placed on its market adoption. Therefore, the current study undertakes survey-based interview research to understand the existing market barriers hindering TES application in buildings. A series of interviews were performed in this study with individuals from various backgrounds, ranging from homeowners to market specialists who work for TES manufacturers and utility companies. According to the responses obtained during the interviews, they strongly believe that TES has a high potential to contribute to the nation's grid stability and decarbonization goals, however, there are several barriers that prevent homeowners and heat pump manufacturers from investing in TES applications. The current study divided the responses from various background groups into categories to better understand the current challenges for TES applications in buildings. These responses range from payback concerns from homeowners to the need to develop a new metric to represent the benefits of TES from the heat pump and TES manufacturers. The findings from this study can be used by policymakers, utility companies, and manufacturers to better understand present obstacles and develop strategies to overcome them.

Prem Anand Jayaprabha, Jyothis Anand↗
DOE OSTI2023

Powder satellite-reduction apparatus and method for gas atomization process

The broad applicability of at least certain aspects of the present invention derives from the ability to determine the critical location where secondary satellite formation occurs for any atomization system or design and allows for the rapid assessment of the effectiveness of various satellite reduction strategies, including but not limited to several embodiments detailed herein. Aspects of this invention can be utilized during initial atomization system design in order to evaluate effective chamber geometries and enabling strategies which reduce/eliminate satelliting, or can be retrofit to existing systems and allows for economic evaluation of effectiveness based off of initial capital expenditures versus increased operating requirements/expenses.

Anderson, Iver E.↗
DOE OSTI2022

Estimation of the NiCu Cycle Strength and Its Impact on Type I X-Ray Bursts

Abstract Type I X-ray bursts (XRBs) are powered by thermonuclear burning on proton-rich unstable nuclides. The construction of burst models with accurate knowledge of nuclear physics is required to properly interpret burst observations. Numerous studies that have investigated the sensitivities of burst models to nuclear inputs have commonly extracted the strength of the NiCu cycle in the rp process, determined by the 59 Cu( p , α ) 56 Ni and 59 Cu( p , γ ) 60 Zn thermonuclear reaction rates, as critical in the determination of reaction flow in the burst. In this study, the strength of the cycle at the XRB temperature range was estimated based on published experimental data. The nuclear properties of the compound nucleus 60 Zn were evaluated for the 59 Cu( p , α ) 56 Ni and 59 Cu( p , γ ) 60 Zn reaction rate calculations. Monte Carlo rate calculations were conducted to include the large uncertainties of nuclear properties in the calculations. In the current work, a weak NiCu cycle is expected, whereas the rates adopted by the previous studies suggest a strong NiCu cycle. Model simulations were performed with the new rates to assess the impact on Type I XRBs. The results show that the estimated cycle strength does not strongly influence the model predictions of the burst light curve or synthesized abundances.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Fused filament fabrication of thermoplastic polyurethane composites with microencapsulated phase-change material

Here, the present study examines the thermal energy storage (TES) effectiveness and printability of microencapsulated phase-change material (MEPCM) combined with thermoplastic polyurethane (TPU) for fused filament fabrication (FFF). Two formulations were assessed: 24D MEPCM, which changes phase at 24 ° C, compounded with TPU pellets and 43D MEPCM, which changes phase at 43 ° C, integrated with TPU powder. These combinations are designed to evaluate the effectiveness of the form of the TPU (pellets versus powder) in the FFF process. The investigation includes a comprehensive analysis of thermal characteristics, encompassing phase-change temperature, latent heat of fusion, thermal conductivity, and thermal decomposition, which are assessed through differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Additionally, mechanical properties, including stress-strain behavior, are examined to evaluate material suitability for TES applications, while microstructural visualization is used to provide deeper insights into material performance, structural integrity, and the quality of printed components. The 24D MEPCM and TPU pellets formulation experienced a significant loss of approximately 39.6% of PCM during filament extrusion and printing, resulting in a reduced effective latent heat. Therefore, further characterization of the pellet formulation was discontinued due to excessive leakage. In contrast, the 43D MEPCM and TPU powder formulation demonstrated minimal PCM loss, with the 60 wt.% composition achieving an effective latent heat of 132 J/g. This value represents the highest effective latent heat currently documented in the literature for PCM-polymer-composite materials produced using an FFF-based additive manufacturing process.

25 ENERGY STORAGE↗
DOE OSTI2024

Machine learning for the redox potential prediction of molecules in organic redox flow battery

Here, organic redox flow batteries (ORFB) are recognized as an innovative technology for the large-scale storage of renewable energy. The redox potential of organic redox-active molecules plays a vital role in their performance. Advanced screening techniques like high-throughput experiment and machine learning (ML) have significantly enhanced organic material performance and transformed the field of ORFB. However, the scarcity of experimental data poses a considerable challenge for ML model development in this domain. In our study, we developed lightweight graph-based Gaussian process regression (GPR) models with GPU-accelerated marginalized graph kernel and hybrid kernel to predict the redox potentials of organic redox-active molecules for ORFBs, specifically focusing on small datasets. To evaluate model accuracy, we created a new experimental database of organic redox-active molecules by the data from hundreds of published papers and assembled previous computational datasets. We also considered some key parameters, such as pH conditions and solvent type, to assess their impact on redox potential prediction. Our GPR model predicted redox potentials with high accuracy across all datasets using minimal training data. The study provides powerful tools for molecule screening and design and delivers valuable guidance on designing training datasets for costly experiments.

25 ENERGY STORAGE↗
DOE OSTI2024

High redshift LBGs from deep broadband imaging for future spectroscopic surveys

Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, z > 2, a region only covered so far by Lyman-α forest measurements. Here, in this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the g, r, z and u bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain 57% of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of 83 ± 3%, for a purity of the selected LBG sample of 90 ± 2%. This would deliver a confirmed LBG density of ~ 620 deg$^{-2}$ in the range 2.3 < z < 3.5 for a r-band limiting magnitude r < 24.2. Selections optimised for high redshift efficiency retain 73% of the observed targets after spectroscopic confirmation, with 89 ± 4% efficiency for 97 ± 2% purity. This would provide a confirmed LBG density of ~ 470 deg$^{-2}$ in the range 2.8 < z < 3.5 for a r-band limiting magnitude r < 24.5.A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of b$_{LBG}$ = 3.3 ± 0.2 (stat.) is obtained for a mean redshift of 2.9 and a limiting magnitude in r of 24.2, in agreement with results reported in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Assessing equation of state-independent relations for neutron stars with nonparametric models

Relations between neutron star properties that do not depend on the nuclear equation of state offer insights on neutron star physics and have practical applications in data analysis. Such relations are obtained by fitting to a range of phenomenological or nuclear physics equation of state models, each of which may have varying degrees of accuracy. In this study we revisit commonly used relations and reassess them with a very flexible set of phenomenological nonparametric equation of state models that are based on Gaussian processes. Our models correspond to two sets: equations of state which mimic hadronic models, and equations of state with rapidly changing behavior that resemble phase transitions. Here we quantify the accuracy of relations under both sets and discuss their applicability with respect to expected upcoming statistical uncertainties of astrophysical observations. We further propose a goodness-of-fit metric which provides an estimate for the systematic error introduced by using the relation to model a certain equation-of-state set. Overall, the nonparametric distribution is more poorly fit with existing relations, with the I–Love–Q relations retaining the highest degree of universality. Fits degrade for relations involving the tidal deformability, such as the binary-Love and compactness-Love relations, and when introducing phase transition phenomenology. For most relations, systematic errors are comparable to current statistical uncertainties under the nonparametric equation of state distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗
DOE OSTI2024

Tackling the Giants: Applying Smart Labs Principles to Constant Air Volume Lab Buildings

Laboratories typically consume 3 to 10 times more energy than similarly sized commercial buildings, and as much as 50% of that energy is wasted by inefficient and poorly operating fume hoods and ventilation systems. One challenge faced by older laboratory buildings is the heating, ventilation, and air-conditioning systems serving many of these buildings. The older systems are usually constant air volume (CAV) systems that maintain constant ventilation rates that cause excess airflow and inefficient energy use. Variable air volume systems can be more efficient systems with sensors to detect the need for a change in volumetric flow rate; however; renovation of ventilation systems can create disruption to ongoing research and operations along with considerable up-front costs. When a Smart Labs program is implemented, an organization has a systems-based management approach that yields a high-performing laboratory building. As decarbonization continues as a priority for sites, buildings with CAV systems are difficult to address. This work centers around practical guidance for improving lab buildings with CAV. In conjunction with industry input on top technology solutions and best practices, recommendations will include performing a laboratory ventilation risk assessment in conjunction with robust retro-commissioning work, which is a crucial step in the Smart Lab process. By applying Smart Labs principles, the aging laboratory building stock of 153,343 (Lawrence Berkeley National Laboratory [LBNL] 2017), comprising roughly 500,000 lab spaces in the United States, can be brought to safe and high-performance operations.

building↗
DOE OSTI2025

Developing tools and process controls to manufacture energy-efficient powders for additive manufacturing feedstocks: Computational analysis of metal powder manufacturing via machining

Traditionally, metal powders have been produced through methods such as grinding, atomization, and electrolysis. In contrast to these techniques, Metal Powder Works, Inc. has pioneered a methodology based on metal cutting. This innovative approach utilizes a vibrating cutting tool to machine metal particles, in the form of chips, from a workpiece. This technique allows for control of powder particle size, morphology, and avoids any thermally induced material changes. This collaboration aims to elucidate metal cutting characteristics and assess performance on tough materials like Inconel alloys. Computational models, using FEA and SPH techniques, will be developed initially, focusing on aluminum alloy (Al 7075-T6) for studying mesh sensitivity, cutting forces, and chip morphology.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators

Abstract. Supercooled liquid clouds are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We take advantage of the Macquarie Island Cloud and Radiation Experiment (MICRE) to perform an analysis of observed and simulated cloud processes over the Southern Ocean in a region and season dominated by supercooled liquid clouds. Using a single-column version of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), we compare two different cloud microphysical schemes to ground-based observations of cloud, precipitation, and radiation over a 2.5-month period (1 January–17 March 2017). Both schemes are able to reproduce aspects of the cloud and radiation observations during MICRE to within the uncertainty of the data when the thermodynamic profile is prescribed with relaxation. There are differences in water mass and representation of reflectivity between the schemes. A sensitivity study of the cloud microphysics schemes, one a bulk one-moment scheme and the other a two-moment scheme with prediction of mass and number, indicates that several key processes create differences between the schemes. Surface radiative fluxes and total water path are highly sensitive to the formation and fall speed of precipitation. The prediction of hydrometeor number with the two-moment scheme yields a better comparison with observed reflectivity and radiative fluxes, despite predicting higher liquid water contents than observed. With the two-moment scheme, we are also able to test the sensitivity of the results to the input of liquid cloud condensation nuclei (CCN) and ice nuclei (IN). The cloud properties and resulting radiative effects are found to be sensitive to the CCN and IN concentrations. More CCN and IN increase liquid and ice water paths, respectively. Thus, both the dynamic environment and aerosols, integrated through the cloud microphysics, are important for properly representing Southern Ocean cloud radiative effects.

58 GEOSCIENCES↗
DOE OSTI2024

Reliability and resilience of environmental flows under uncertainty: reconsidering water year types and inconsistent flow requirements in California

Abstract Environmental water allocation in California is a complex legal process involving various government agencies and stakeholders. E-flow requirements can be based on annual runoff typologies called water year types (WYTs), which dictate water volume, timing, and duration. In this study, we examined hydropower licensing documents of the major water and power projects in the Central Sierra Nevada to catalog e-flow requirements by WYT. In this study case, we identify how WYT classification systems and categories vary across and within different basins. Additionally, we assessed the impacts of climate change on hydrology, the frequency of WYTs identified, and the reliability and resilience of e-flows using future projections (2031–2060) of 10 Global Circulation Models (GCMs). We then propose a potential adaptation strategy using a 30 year moving percentiles approach to recalculate WYTs. We identified eight WYT classifications systems were identified, and their WYT distributions statistically significantly changes across all GCMs, even though most GCMs indicate no statistically significant change in hydrology. Disparities in future impacts are observed among and within hydropower projects, with some river reaches showing negative impacts on reliability and resilience. The adaptation strategy can generally boost resilience and improve reliability, but simply updating existing WYT thresholds without flexible regulatory frameworks reconsidering WYTs and e-flows thresholds, may not yield substantial improvements. Challenges in managing e-flows in California within regulatory and hydroclimatic contexts are intricate due to the lack of standardized approaches, leading to inconsistencies and potential conflicts among stakeholders, that will likely be exacerbated by climate change. Thus, we emphasize that targeted, site-specific, and adaptive management strategies are crucial, besides the need for a harmonized and consistent approach to defining and applying WYT categories and methods and/or e-flow assessments.

Environmental Sciences & Ecology↗
DOE OSTI2020

A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Long-term nitrogen deposition enhances microbial capacities in soil carbon stabilization but reduces network complexity

Background: Anthropogenic activities have increased the inputs of atmospheric reactive nitrogen (N) into terrestrial ecosystems, affecting soil carbon stability and microbial communities. Previous studies have primarily examined the effects of nitrogen deposition on microbial taxonomy, enzymatic activities, and functional processes. Here, we examined various functional traits of soil microbial communities and how these traits are interrelated in a Mediterranean type grassland administrated with 14 years of 7 g m –2 year –1 of N amendment, based on estimated atmospheric N deposition in areas within California, USA, by the end of the twenty-first century. Results: Soil microbial communities were significantly altered by N deposition. Consistent with higher aboveground plant biomass and litter, fast-growing bacteria, assessed by abundance-weighted average rRNA operon copy number, were favored in N deposited soils. The relative abundances of genes associated with labile carbon (C) degradation (e.g., amyA and cda) were also increased. In contrast, the relative abundances of functional genes associated with the degradation of more recalcitrant C (e.g., mannanase and chitinase) were either unchanged or decreased. Compared with the ambient control, N deposition significantly reduced network complexity, such as average degree and connectedness. The network for N deposited samples contained only genes associated with C degradation, suggesting that C degradation genes became more intensely connected under N deposition. Conclusions: We propose a conceptual model to summarize the mechanisms of how changes in above- and belowground ecosystems by long-term N deposition collectively lead to more soil C accumulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spectro-Microscopy Studies of Atmospheric Particles

Our project investigated composition and physical properties of individual atmospheric particles collected in field campaigns organized by the DOE Atmospheric Systems Research and Atmospheric Radiation Measurement (ASR/ARM) programs, such as the Green Ocean Amazon (GoAmazon, 2014/5), the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE, 2016/7), the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA, 2017/8), the Aerosol–Ice Formation Closure Pilot Study (AEROICESTUDY, 2019) and in additional small-scale supporting field experiments focused on the investigation of the light-absorbing (aka brown carbon) atmospheric particles. In these studies, we investigated the contribution of natural and anthropogenic sources to populations of atmospheric particles during representative atmospheric conditions; characterized particle composition and evaluated their hygroscopic properties and propensity to act as cloud condensation nuclei (CCN) and ice nuclei (IN); correlated typical particle-type and mixing state characteristics with real-time measurements in the areas of studies. We used multi-modal spectro-microscopy techniques to examine elemental and molecular composition, mixing state, size, and higher order morphology for individual particles. Specifically, we used computer-controlled scanning electron microscopy and X-ray microanalysis for quantitative analysis of particle elemental composition, and we used transmission electron microscopy to provide additional information on the distribution of different components within individual particles (particle heterogeneity). We used synchrotron-based scanning transmission X-ray microscopy for quantitative description of the mixing state and molecular bonding of carbon in particles. The particle composition, mixing state, and morphology from analyzed periods was then combined with the real-time ARM measurements of aerosol size distribution, CCN concentration, hygroscopicity, and aerosol bulk composition. Combined together, results of our studies allowed us to assess the major particle sources (biogenic vs. anthropogenic, primary vs secondary) and gain insight into the atmospheric processing of aerosol particles resulting from condensation, coagulation, oxidative aging, and cloud processing. In collaboration with other scientists involved in field campaigns, we carried out statistical analysis of particle properties and their source-specific contributions to regional aerosol loading under representative air mass, meteorological, and cloud conditions.

scanning transmission X-ray microscopy↗