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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine Learning Downscaling of SoilMERGE in the United States Southern Great Plains

SoilMERGE (SMERGE) is a root-zone soil moisture (RZSM) product that covers the entire continental United States and spans 1978 to 2019. Machine learning techniques, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Gradient Boost (GBoost) downscaled SMERGE to spatial resolutions straddling the field scale domain (100 to 3000 m). Study area was northern Oklahoma and southern Kansas. The coarse resolution of SMERGE (0.125 degree) limits this product’s utility. To validate downscaled results in situ data from four sources were used that included: United States Department of Energy Atmospheric Radiation Measurement (ARM) observatory, United States Climate Reference Network (USCRN), Soil Climate Analysis Network (SCAN), and Soil moisture Sensing Controller and oPtimal Estimator (SoilSCAPE). In addition, RZSM retrievals from NASA’s Airborne Microwave Observatory of Subcanopy and Surface (AirMOSS) campaign provided a nearly spatially continuous comparison. Three periods were examined: era 1 (2016 to 2019), era 2 (2012 to 2015), and era 3 (2003 to 2007). During eras 1 and 2, RF outperformed XGBoost and GBoost, whereas during era 3 no model dominated. Performance was better during eras 1 and 2 as opposed to the pre-L band era 3. Improvements across all eras, regions, and models realized from downscaling included an increase in correlation from 0.03 to 0.42 and a decrease in ub RMSE from -0.0005 to -0.0118 m 3 /m 3 . This study demonstrates the feasibility of SMERGE downscaling opening the prospect for the development of a long-term RZSM dataset at a more desirable field-scale resolution with the potential to support diverse hydrometeorological and agricultural applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Human myoblasts differentiate in various mesenchymal lineages and inhibit allogeneic T cell proliferation through an indolamine 2,3 dioxygenase dependent pathway

Muscle stem cells (MuSC) are considered as a reliable source of therapeutic cells to restore diseased muscles. However in most cases, injected MuSC-derived myoblasts are rapidly destroyed by the host immune response, which impairs the beneficial effect. By contrast, human mesenchymal stromal cells (MSC), have been reported to exhibit potent immune regulatory functions. Thus, we investigated, in vitro, the multipotent differentiation- and immunosuppressive capacities of human myoblasts and compared these features with those of human MSC. Myoblasts shared numerous cell surface markers with MSC, including CD73, CD90, CD105 and CD146. Both cell type were negative for HLA-DR and CD45, CD34 and CD31. CD56, a myogenic marker, was expressed by myoblasts exclusively. Myoblasts displayed multipotent potential capabilities with differentiation in chondrocytes, adipocytes and osteoblasts in vitro. Myoblasts also inhibited allogenic T cell proliferation in vitro in a dose dependent manner, very similarly to MSC. This effect was partly mediated via the activation of indolamine 2,3 dioxygenase enzyme (IDO) after IFNγ exposure. Altogether, these data demonstrate that human myoblasts can differentiate in various mesenchymal linages and exhibit powerful immunosuppressive properties in vitro. Such features may open new therapeutic strategies for MuSC-derived myoblasts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Conceptual design of the time-of-flight backscattering spectrometer, MIRACLES, at the European Spallation Source

In this work, we present the conceptual design of the backscattering time-of-flight spectrometer MIRACLES approved for construction at the long-pulse European Spallation Source (ESS). MIRACLES’s unparalleled combination of variable resolution, high flux, extended energy, and momentum transfer (0.2–6 Å{sup −1}) ranges will open new avenues for neutron backscattering spectroscopy. Its remarkable flexibility can be attributed to 3 key elements: the long-pulse time structure and low repetition rate of the ESS neutron source, the chopper cascade that tailors the moderator pulse in the primary part of the spectrometer, and the bent Si(111) analyzer crystals arranged in a near-backscattering geometry in the secondary part of the spectrometer. Analytical calculations combined with instrument Monte-Carlo simulations show that the instrument will provide a variable elastic energy resolution, δ(ħ ω), between 2 and 32 μeV, when using a wavelength of λ ≈ 6.267 Å (Si(111)-reflection), with an energy transfer range, ħ ω, centered at the elastic line from −600 to +600 μeV. In addition, when selecting λ ≈ 2.08 Å (i.e., the Si(333)-reflection), δ(ħ ω) can be relaxed to 300 μeV and ħ ω from about 10 meV in energy gain to ca −40 meV in energy loss. Finally, the dynamic wavelength range of MIRACLES, approximately 1.8 Å, can be shifted within the interval of 2–20 Å to allow the measurement of low-energy inelastic excitations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Lacustrine leaf wax hydrogen isotopes indicate strong regional climate feedbacks in Beringia since the last ice age

The Late-Quaternary climate of Beringia remains unresolved despite the region's role in modulating glacial-interglacial climate and as the likely conduit for human dispersal into the Americas. In this work, we investigate Beringian temperature change using an ~32,000-year lacustrine record of leaf wax hydrogen isotope ratios (δ2Hwax) from Arctic Alaska. Based on Monte Carlo iterations accounting for multiple sources of uncertainty, the reconstructed summertime temperatures were ~3 °C colder (range: –8 to +3 °C) during the Last Glacial Maximum (LGM; 21-25 ka) than the pre-industrial era (PI; 2–0.1 ka). This ice-age summer cooling is substantially smaller than in other parts of the Arctic, reflecting altered atmospheric circulation and increased continentality which weakened glacial cooling in the region. Deglacial warming was punctuated by abrupt events that are largely synchronous with events seen in Greenland ice cores that originate in the North Atlantic but which are also controlled locally, such as by the opening of the Bering Strait between 13.4 and 11 ka. Our reconstruction, together with climate modeling experiments, indicates that Beringia responds more strongly to North Atlantic freshwater forcing under modern-day, open-Bering Strait conditions than under glacial conditions. Furthermore, a 2 °C increase (Monte Carlo range: –1 to +5 °C) over the anthropogenic era reverses a 6 °C decline (Monte Carlo range: –10 to 0 °C) through the Holocene, indicating that recent warming in Arctic Alaska has not surpassed peak Holocene summer warmth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Progress in the development of the community Particle Accelerator Lattice Standard (PALS)

The Particle Accelerator Lattice Standard (PALS) is a community effort to create an open standard to promote lattice information exchange for particle accelerators. PALS development is a community-wide international effort involving accelerator physicists from multiple institutions. While it started as a lattice standard for beam dynamics simulations, it is now being extended to support other particle accelerator activities, in particular accelerator operation. With new accelerators that are becoming more complex, larger collaborations and the increasing imprint of artificial intelligence in all accelerator activities (from design to operation to workforce development), the imperative for a common, standardized accelerator ontology has been transitioning from “nice-to-have” to “must-have”. We will present the status of the project, its relations to other projects, including to two of the particle accelerator projects of the newly announced US DOE Genesis Mission: the Multi-Office Accelerator Team (MOAT) project and the Nuclear physics AI-Ready Accelerator Data (NARAD) project.

Brynes, A. [Science and Technology Facilities Coun↗
DOE OSTI2019

Positive-ion accelerator mass spectrometry at ATLAS: Peaks and pits

Electron Cyclotron Resonance (ECR) ion sources and the production of multiple-charge positive ions with high efficiency in combination with a heavy-ion accelerator have opened the way to an alternative and complementary version of accelerator mass spectrometry (AMS). A notable strength of positive-ion over traditional AMS is the capability of ultra-high sensitivity detection of radioactive isotopes of noble gases, in particular 37 Ar (t 1/2 = 35 d) and 39 Ar (269 y). The complete dissociation of molecular ions in the ECR and in particular of hydride ions of neighboring stable isotopes results in superior isotopic separation. However, the use of high charge states, necessary for acceleration to high energy, entails the existence of severe transmission degeneracies with stable ions having nearly equal mass-to-charge ratios, in addition to that of stable isobaric ions. Separation or discrimination of these parasitic ions require powerful and sophisticated dispersive systems at detection stage. In conclusion, we review here work performed and in progress at the ATLAS facility of Argonne National Laboratory (ANL) where an ECR ion source, a Radio-Frequency Quadrupole (RFQ), a superconducting linear accelerator and a Gas-Filled Magnet (GFM) are used as an AMS setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Beyond a phenomenological description of magnetostriction

Magnetostriction, the strain induced by a change in magnetization, is a universal effect in magnetic materials. Owing to the difficulty in unraveling its microscopic origin, it has been largely treated phenomenologically. Here in this paper, we show how the source of magnetostriction—the underlying magnetoelastic stress—can be separated in the time domain, opening the door for an atomistic understanding. X-ray and electron diffraction are used to separate the sub-picosecond spin and lattice responses of FePt nanoparticles. Following excitation with a 50-fs laser pulse, time-resolved X-ray diffraction demonstrates that magnetic order is lost within the nanoparticles with a time constant of 146 fs. Ultrafast electron diffraction reveals that this demagnetization is followed by an anisotropic, three-dimensional lattice motion. Analysis of the size, speed, and symmetry of the lattice motion, together with ab initio calculations accounting for the stresses due to electrons and phonons, allow us to reveal the magnetoelastic stress generated by demagnetization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Extreme Compression for Large Scale Data Store

For the last 5 years Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom line outcome would be to provide a state-of-the-art compression algorithm that surpasses those currently available in the ROOT framework, with the purpose of enabling substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4.In this contribution, we will present our concepts of “functionally lossless compression”, have a glance at examples and achievements in other communities, present the results and outcome of our current, ongoing R&D, as well as present a high-level view of our plan to move forward with a ROOT implementation that would deliver a basic solution readily integrated into HENP applications. As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Considerations for the Design of a Gas Transport System for Co-location of Microalgae Cultivation with CO 2 Sources

Co-locating microalgae cultivation facilities with sources of waste CO 2 may present opportunities for cost savings that could benefit the algal biomass industry and industries or utilities that have incentives to manage carbon emissions. However, the cost savings have not been quantified. We compare the cost of utilizing CO 2 from flue gas transported to 405-ha, base-case, open-pond microalgae facilities to the commercial purchase price of CO 2 . Sources of CO 2 include coal- and natural gas-fired power plants and ethanol, ammonia, and cement production plants in the United States. The transport of CO 2 -containing gases to the microalgae cultivation facility requires infrastructure and electricity. This engineering analysis explores the parameters that affect the infrastructure and transport distance over which emitted flue gases can be cost-effectively transported to microalgae cultivation facilities, compared to the cost of commercially purchased CO 2 (i.e., the break-even distance). Parameters that are varied include size of facility pond area, productivity, and daily duration of waste CO 2 emissions that are transported to algae. Under our assumptions and under all cases in this study, cost savings can be achieved by co-locating microalgae facilities near waste CO 2 sources. The break-even distance, which is estimated here to range from under 2 to 80 km, depends primarily on the concentration of CO 2 in flue gas, algae productivity, facility size, and pipeline system design considerations. Greater break-even distances are simulated if electricity cost is minimized, rather than if capital cost is minimized.

09 BIOMASS FUELS↗
DOE OSTI2024

A method for crystallographic mapping of an alpha-beta titanium alloy with nanometre resolution using scanning precession electron diffraction and open-source software libraries

An approach for the crystallographic mapping of two-phase alloys on the nanoscale using a combination of scanned precession electron diffraction and open-source python libraries is introduced in this paper. This method is demonstrated using the example of a two-phase α/β titanium alloy. The data were recorded using a direct electron detector to collect the patterns, and recently developed algorithms to perform automated indexing and analyse the crystallography from the results. Very high-quality mapping is achieved at a 3 nm step size. The results show the expected Burgers orientation relationships between the α laths and β matrix, as well as the expected misorientations between α laths. A minor issue was found that one area was affected by 180° ambiguities in indexing occur due to this area being aligned too close to a zone axis of the α with twofold projection symmetry (not present in 3D) in the zero-order Laue Zone, and this should be avoided in data acquisition in the future. Nevertheless, this study demonstrates a good workflow for the analysis of nanocrystalline two- or multi-phase materials, which will be of widespread use in analysing two-phase titanium and other systems and how they evolve as a function of thermomechanical treatments.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-J-153: Reconstructing 4D Cone Beam CT Images for Clinical QA of Lung SABR Treatments

Purpose: To verify that the planned Primary Target Volume (PTV) and Internal Gross Tumor Volume (IGTV) fully enclose a moving lung tumor volume as visualized on a pre-SABR treatment verification 4D Cone Beam CT. Methods: Daily 3DCBCT image sets were acquired immediately prior to treatment for 10 SABR lung patients using the on-board imaging system integrated into a Varian TrueBeam (v1.6: no 4DCBCT module available). Respiratory information was acquired during the scan using the Varian RPM system. The CBCT projections were sorted into 8 bins offline, both by breathing phase and amplitude, using in-house software. An iterative algorithm based on total variation minimization, implemented in the open source reconstruction toolkit (RTK), was used to reconstruct the binned projections into 4DCBCT images. The relative tumor motion was quantified by tracking the centroid of the tumor volume from each 4DCBCT image. Following CT-CBCT registration, the planning CT volumes were compared to the location of the CBCT tumor volume as it moves along its breathing trajectory. An overlap metric quantified the ability of the planned PTV and IGTV to contain the tumor volume at treatment. Results: The 4DCBCT reconstructed images visibly show the tumor motion. The mean overlap between the planned PTV (IGTV) and the 4DCBCT tumor volumes was 100% (94%), with an uncertainty of 5% from the 4DCBCT tumor volume contours. Examination of the tumor motion and overlap metric verify that the IGTV drawn at the planning stage is a good representation of the tumor location at treatment. Conclusion: It is difficult to compare GTV volumes from a 4DCBCT and a planning CT due to image quality differences. However, it was possible to conclude the GTV remained within the PTV 100% of the time thus giving the treatment staff confidence that SABR lung treatements are being delivered accurately.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Enabling Load Following Capability in the Transatomic Power MSR

This project is dedicated towards designing a fuel processing system that enables liquid-fueled molten salt reactors (MSR) to load follow by removing the dissolved xenon in the fuel salt. As one of the Gen-IV nuclear reactor concepts, the molten salt reactor receives increasing development interests in the recent years. One distinguishing feature of the liquid-fueled molten salt reactor is its improved ability to operate in a load-following mode by including the unique online fission product removal system. Load-following means that the reactor changes its power output based on the demand on the grid. Most of the current operating nuclear reactors have limited load-following ability and operate as the base load on the grid. Due to the rapid increase of solar energy, the requirement on load-following capacity is significantly increased because of the varying power output of the solar panels, yet the traditional load-following capacity is expected to decrease as the decarbonization of the grid continues. Therefore, the ability to perform load-following operation for the nuclear reactors will greatly enhance the resilience of the grid and make nuclear energy more economically competitive. This load-following feature is included in many commercial molten salt reactor designs, such as the designs by Transatomic Power, Terrestrial Energy, and Flibe Energy. Unfortunately, detailed analysis of the fuel processing system for commercial scale MSRs is still lacking, as well as how the fuel processing quantitively impacts the load-following operation. Moreover, experimental data for many of the underlying physics of fuel processing is limited. This project aims to pave the way for the fuel processing technology to advance to the commercial stage by performing combined experimental and simulation research. During the project period, four interconnected aspects of the development of the fuel processing system in liquid-fueled molten salt reactors are investigated. These aspects are the simulation and analysis of the fission product removal system, the fuel cycle simulation, the coupled reactor neutronics and thermal hydraulics transient simulation, and the gaseous fission product removal experiment. Multiphase CFD simulations are performed for components of the processing systems, and simplified air-water experiments are carried out to provide validation data. It is concluded that the CFD simulation can satisfactorily predict the system level performance of the components, and engineering models are constructed based on this success. Fuel cycle analysis is performed for two representative MSR design, the MSBR and the Transatomic Power MSR. Open-source code SaltProc is developed to incorporate the unique fuel processing system of the MSRs. It is concluded that the removal of xenon is essential for load-following operation in thermal spectrum MSR and Molten Salt Breeder Reactor. For the Transatomic Power MSR, the xenon poisoning effect is negligible due to its relatively fast neutron spectrum, though the overall fuel cycle economics still benefits from the removal of xenon. Coupled reactor neutronics and thermal hydraulics transient simulation is performed specifically for the Transatomic Power MSR. It is concluded that the reactor core design could perform power ramping fast enough to satisfy load-following operation. Combining the findings from each aspect, it is concluded that the load-following operation of a thermal neutron MSR is dependent upon the removal of xenon, which could be achieved for a commercial sized reactor using continuous inert gas sparging in a separate system with reasonable dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

TU-H-BRC-05: Stereotactic Radiosurgery Optimized with Orthovoltage Beams

Purpose: To achieve improved stereotactic radiosurgery (SRS) dose distributions using orthovoltage energy fluence modulation with inverse planning optimization techniques. Methods: A pencil beam model was used to calculate dose distributions from the institution’s orthovoltage unit at 250 kVp. Kernels for the model were derived using Monte Carlo methods as well as measurements with radiochromic film. The orthovoltage photon spectra, modulated by varying thicknesses of attenuating material, were approximated using open-source software. A genetic algorithm search heuristic routine was used to optimize added tungsten filtration thicknesses to approach rectangular function dose distributions at depth. Optimizations were performed for depths of 2.5, 5.0, and 7.5 cm, with cone sizes of 8, 10, and 12 mm. Results: Circularly-symmetric tungsten filters were designed based on the results of the optimization, to modulate the orthovoltage beam across the aperture of an SRS cone collimator. For each depth and cone size combination examined, the beam flatness and 80–20% and 90–10% penumbrae were calculated for both standard, open cone-collimated beams as well as for the optimized, filtered beams. For all configurations tested, the modulated beams were able to achieve improved penumbra widths and flatness statistics at depth, with flatness improving between 33 and 52%, and penumbrae improving between 18 and 25% for the modulated beams compared to the unmodulated beams. Conclusion: A methodology has been described that may be used to optimize the spatial distribution of added filtration material in an orthovoltage SRS beam to result in dose distributions at depth with improved flatness and penumbrae compared to standard open cones. This work provides the mathematical foundation for a novel, orthovoltage energy fluence-modulated SRS system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The LAKE model input dataset for three Arctic lakes

This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Shoreline wave breaking strongly enhances the coastal sea spray aerosol population: Climate and air quality implications

Sea spray aerosol (SSA) emission is a major source of atmospheric aerosols, influencing global climate and coastal air quality. Much of our knowledge about SSA derives from coastal observations near shorelines, but whether and when these observations accurately represent open oceans remain unclear. Here, we show that strong nearshore SSA production during high-wave periods greatly enhances downwind cloud condensation nuclei (CCN) and aerosol mass concentrations. Strong shoreline wave breaking is widespread globally, and swell waves, which are decoupled from local winds, play a dominant role in many coastal regions. Therefore, extrapolating results based on coastal measurements to open oceans may significantly overestimate SSA concentration and its contribution to CCN and, by extension, the impact of SSA on clouds and climate. Additionally, the strong enhancement of coastal aerosol population by shoreline wave breaking and its environmental impact on coastal communities cannot be captured by current regional models, which do not parameterize nearshore SSA generation using wave energy or completely neglect it.

54 ENVIRONMENTAL SCIENCES↗