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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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14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Analysis of contrasting aerosol indirect effects in liquid water clouds over the northern part of Arabian Sea

The extensive daily statistics of aerosol properties, cloud properties, and their mutual correlations provide crucial information for better assessing future climate change. Here, in this paper, 14 years (2010–2023) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are analyzed over the northern part of Arabian Sea (Latitude: 21°–25° N and Longitude: 62°–68° E) to assess the characteristics of aerosols and clouds and their relationships under different meteorological conditions. When aerosol optical depth (AOD) is less than ~0.7, the observations exhibit a positive correlation between AOD and cloud droplet effective radius (CDR) but negative correlations between AOD and cloud droplet number concentration (CDNC), between AOD and cloud optical depth (COD), between AOD and cloud liquid water path (CLWP), and between AOD and cloud geometrical thickness (H). The corresponding aerosol-cloud correlations change signs when the AOD values are larger than 0.7. However, the single folded positive AOD-cloud fraction (CF) relationship is observed in both AOD regimes. Similar correlations are also observed between precipitable water vapor (PWV) and CDR, CDNC, COD, H, CF and CLWP, together with a positive correlation between PWV and AOD. Further isolation of the environmental effects from aerosol effects by stratifying AOD and cloud data into different LTS and PWV bins shows that the signature of the well-known Twomey effect is observed under high LTS-high PWV conditions, while an opposite effect (anti-Twomey) is observed under low PWV conditions, regardless of LTS values. Additionally, negative correlations between AOD and COD, AOD and CLWP, and AOD and H are observed under low LTS, regardless of PWV conditions, with a slight positive correlation when AOD >0.4 under high LTS and PWV conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Two decades of aerosol trends over India: seasonal characteristics and urban-rural dynamics

Abstract India faces significant air quality challenges, with one of the highest air pollution levels of any country in the world. Here, we examine two decades (2001–2019) of both particulate matter (PM 2.5 ) concentration and aerosol optical depth (AOD) over the country. Increases are seen between the two decadal averages, for 2001–2010 and 2011–2019, in western India, particularly in the Indo-Gangetic Plain (IGP). IGP region, including Bihar, West Bengal, Jharkhand, and Uttar Pradesh, shows the highest increases in AOD (+0.03, 13%) and PM 2.5, s (+8 µ g m −3 ). Seasonal AOD patterns fluctuate, with the IGP experiencing the highest wintertime increase, especially in Bihar (+0.07). In summer, there are increases in AOD along the southern and eastern coastal areas. Monsoons cause a slight rise in AOD, except in Rajasthan. In the post-monsoon season, the IGP experiences a notable increase in AOD (+0.057, 25%), potentially driven by biomass burning in Bihar (+0.11) and Uttar Pradesh (+0.075). Dividing our study area into urban and peri-urban clusters ( n = 2791), AOD is found to be similar, possibly due to advective mixing. However, the differences between urban and rural areas become more noticeable, especially in the second decade. Correlations between AOD and PM 2.5, g vary across locations, with the highest found in Kanpur ( R 2 = 0.61) and weaker in Delhi ( R 2 = 0.42), highlighting the need for more ground monitoring. However, it suggests that satellite-derived AOD can generally be used to examine trends in PM 2.5 over longer time frames.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories

We assessed the biomass burning (BB) smoke aerosol optical depth (AOD) simulations of 11 global models that participated in the AeroCom phase III BB emission experiment. By comparing multi-model simulations and satellite observations in the vicinity of fires over 13 regions globally, we (1) assess model-simulated BB AOD performance as an indication of smoke source–strength, (2) identify regions where the common emission dataset used by the models might underestimate or overestimate smoke sources, and (3) assess model diversity and identify underlying causes as much as possible. Using satellite-derived AOD snapshots to constrain source strength works best where BB smoke from active sources dominates background non-BB aerosol, such as in boreal forest regions and over South America and southern hemispheric Africa. The comparison is inconclusive where the total AOD is low, as in many agricultural burning areas, and where the background is high, such as parts of India and China. Many inter-model BB AOD differences can be traced to differences in values for the mass ratio of organic aerosol to organic carbon, the BB aerosol mass extinction efficiency, and the aerosol loss rate from each model. The results point to a need for increased numbers of available BB cases for study in some regions and especially to a need for more extensive regional-to-global-scale measurements of aerosol loss rates and of detailed particle microphysical and optical properties; this would both better constrain models and help distinguish BB from other aerosol types in satellite retrievals. More generally, there is the need for additional efforts at constraining aerosol source strength and other model attributes with multi-platform observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Advancing the quantification of aerosol-cloud interactions with the CALIPSO-CloudSat-Aqua/MODIS record

Aerosol-cloud-precipitation interactions are assessed over the non-polar ocean using more than 11 years of combined Aqua-MODIS, CALIPSO-CALIOP, and CloudSat products. The analysis first shows the benefit of incorporating vertically resolved aerosol extinction coefficient (σext) in aerosol-cloud interactions (ACI) assessments, demonstrating that: σext vertically collocated with the cloud layer () correlates best with cloud droplet number concentration (Nd), column-integrated aerosol optical depth (AOD) cannot explain the Nd variability in the extratropics, and the S-shape of the AOD-Nd relationship reported in previous studies is not replicated when using instead of AOD, with a Nd- linearity more consistent with in-situ studies over the ocean. ACI metric, estimated as the log-scale regression between CALIOP and MODIS Nd reveals that the eastern Pacific is the region with the strongest ACI, followed by the Southern Ocean. The susceptibility of clouds to changes in their liquid water path (LWP) and frequency of precipitation followed a 2-step calculation by combining the Nd- regression (ACI) with the regression between these macrophysical variables and Nd. LWP susceptibility is negative (LWP decreases with aerosol loading) and statistically significant over the eastern Pacific, eastern Atlantic, and extratropics. In contrast, vast areas of the tropical and subtropical ocean feature negligible changes in LWP with aerosol. Precipitation frequency susceptibility is negative, but the values are only significant over the coastal eastern Pacific and Atlantic. The findings suggest that previous modeling assessments relying on AOD may need to be revisited by taking advantage of the synergy between passive and active sensors.

Li, Zhujun↗
DOE OSTI2025

MODIS Aerosol and Low‐Cloud Retrievals: Orographic Effects in the Wake of Macquarie Island

Abstract Visible/infrared imagery from passive satellites is commonly relied upon to study low cloud microphysics over oceanic regions, including for the Southern Ocean (SO), but relatively little validation has been undertaken for the SO. In this article, we compare low‐cloud effective radius ( r e ), cloud droplet number concentration ( N d ) and cloud liquid water path (LWP) retrievals from the NASA Moderate Imaging Spectroradiometer (MODIS) with surface measurements collected during the Macquarie Island Cloud and Radiation Experiment (MICRE). MODIS 3.7‐μm band retrievals show little bias and moderately good correlation relative to MICRE retrievals for liquid‐phase low clouds when restricted to Solar Zenith Angles <65° on spatial scales of 50–100 km. However, the low overall bias in 3.7‐μm band effective radius ( r e 3.7 ) retrievals partly results from cancellation of errors: r e 3.7 is overestimated for non‐to‐lightly precipitating clouds, and underestimated for heavier drizzling clouds by ∼1–1.5 μm. 1.6‐μm and 2.1‐μm band r e retrievals are biased high. N d may likewise be slightly under‐ or overestimated depending on the concentration, but there is insufficient data to provide confidence in this result. Interestingly, a composite of MODIS retrievals from 2002 to 2020 show a distinct region of enhanced cloud cover and N d (and lower r e ) in the wake of Macquarie Island associated with orographic cloud formation. MODIS retrievals of aerosol optical depth (AOD) and Angstrom Exponent (AE) upwind and downwind of the island do not differ significantly. Comparison with MICRE measurements suggests that MODIS Collection 6 AOD retrievals are reasonable, while AE is problematically large.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sensitivity of Regional WRF‐Chem Air Quality and Weather Simulations to Biomass‐Burning Emission Data Sets: A Case Study of the Impact of Canadian Wildfire on the US°

This study focuses on the period from June 26 to 29, 2023, when record‐breaking Canadian wildfires severely impacted air quality in the Midwest United States. Using the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) and four biomass‐burning data sets (Fire Inventory from NCAR version 1, Fire Inventory from NCAR version 2.5, Quick Fire Emissions Data set [QFED], and Regional ABI‐VIIRS Emission), we analyzed aerosol transport from Canada to the US and assessed the model's accuracy in predicting PM 2.5 , O 3 , CO and aerosol weather feedback. Model simulations were compared with ground‐based and remote sensing observations as well as field measurements from the Community Research on Climate and Urban Science (CROCUS) project. Our findings show that the movement of a low‐pressure system from the Great Lakes to the Atlantic, combined with the high‐pressure system over the Atlantic, caused the transport of aerosols from Canadian wildfires to the US. Results show WRF‐Chem significantly underestimated key atmospheric components: aerosol optical depth (AOD) by over 50%, PM 2.5 by 65%–90% and peak O 3 concentrations by 50%–55% across four biomass burning data sets. Additionally, CO and NO 2 concentrations were underpredicted. The substantial underestimation of PM 2.5 led to an overestimation of temperature by up to 3.6 °C primarily due to excessive downward shortwave radiation, which resulted from the underestimation of direct aerosol effects and an increase in sensible heat flux. Among the biomass‐burning data sets, QFED produced the most accurate AOD and PM 2.5 predictions due to improved wildfire emission estimates, leading to a 1.0 to 1.5 °C reduction in temperature overestimation during the daytime. These findings underscore the need for improving wildfire emission estimates for trace gases and aerosols to enhance air quality and weather feedback predictions.

WRF-chem model↗
DOE OSTI2025

Radiative impact of record-breaking wildfires from integrated ground-based data

The radiative effects of wildfires have been traditionally estimated by models using radiative transfer calculations. Assessment of model-predicted radiative effects commonly involves information on observation-based aerosol optical properties. However, lack or incompleteness of this information for dense plumes generated by intense wildfires reduces substantially the applicability of this assessment. Here we introduce a novel method that provides additional observational constraints for such assessments using widely available ground-based measurements of shortwave and spectrally resolved irradiances and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges. We apply our method to quantify the radiative impact of the record-breaking wildfires that occurred in the Western US in September 2020. For our quantification we use integrated ground-based data collected at the Atmospheric Measurements Laboratory in Richland, Washington, USA with a location frequently downwind of wildfires in the Western US. We demonstrate that remarkably dense plumes generated by these wildfires strongly reduced the solar surface irradiance (up to 70% or 450 Wm -2 for total shortwave flux) and almost completely masked the sun from view due to extremely large AOD (above 10 at 500 nm wavelength). We also demonstrate that the plume-induced radiative impact is comparable in magnitude with those produced by a violent volcano eruption occurred in the Western US in 1980 and continental cumuli.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Astigmatism-free 3D optical tweezer control for rapid atom rearrangement

Reconfigurable neutral-atom arrays are a promising platform for quantum computing, quantum simulation, and quantum metrology, but atom transport using frequency-chirped acousto-optic deflectors (AODs) is limited by chirp-induced acoustic lensing and trajectory distortion. We address these limitations using a three-dimensional acousto-optic deflector lens (3D-AODL), a design predicted to reduce long-range transport times by more than a factor of two. We further introduce fading-Shepard waveforms that circumvent finite AOD bandwidth, enabling sustained axial displacement. We demonstrate unrestricted three-dimensional optical-tweezer motion over a 200 μm × 200 μm × 136 μm volume with velocities exceeding 4.2 m/s. Arbitrary three-dimensional control of optical-tweezer trajectories enables rapid atom rearrangement and dynamical engineering of optical potentials in tweezer arrays and optical lattices. This capability advances quantum control and atom manipulation in neutral-atom quantum processors by enabling faster rearrangement, higher clock rates, and scalable sorting in complex geometries.

Lu, Yue-Hui [University of California, Berkeley, C↗
DOE OSTI2024

Quantifying the impacts of marine aerosols over the southeast Atlantic Ocean using a chemical transport model: implications for aerosol–cloud interactions

The southeast Atlantic region, characterized by persistent stratocumulus clouds, has one of the highest uncertainties in aerosol radiative forcing and significant variability across climate models. In this study, we analyze the seasonally varying role of marine aerosol sources and identify key uncertainties in aerosol composition at cloud-relevant altitudes over the southeast Atlantic using the GEOS-Chem chemical transport model. We evaluate simulated aerosol optical depth (AOD) and speciated aerosol concentrations against those collected from ground observations and aircraft campaigns such as LASIC, ORACLES, and CLARIFY, conducted during 2017. The model consistently underestimates AOD relative to AERONET, particularly at remote locations like Ascension Island. However, when compared with aerosol mass concentrations from aircraft campaigns during the biomass burning period, it performs adequately at cloud-relevant altitudes, with a normalized mean bias (NMB) between -3.5 % (CLARIFY) and -7.5 % (ORACLES). At these altitudes, in the model, organic aerosols (63 %) dominate during the biomass burning period, while sulfate (41 %) prevails during austral summer, when dimethylsulfide (DMS) emissions peak in the model. Our findings indicate that marine sulfate can account for up to 69 % of total sulfate during the high-DMS period. Sensitivity analyses indicate that refining DMS emissions and oxidation chemistry may increase sulfate aerosol produced from marine sources, highlighting that there remains large uncertainty as to the role of DMS emissions in the marine boundary layer. Additionally, we find marine primary organic aerosol emissions may substantially increase total organic aerosol concentrations, particularly during austral summer. This study underscores the imperative need to refine marine emissions and their chemical transformations, as aerosols from marine sources are a major component of total aerosols at cloud-relevant altitudes and may impact uncertainties in aerosol radiative forcing over the southeast Atlantic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Size-resolved process understanding of stratospheric sulfate aerosol following the Pinatubo eruption

Stratospheric sulfate aerosol produced by volcanic eruptions plays important roles in atmospheric chemistry and the global radiative balance of the atmosphere. The simulation of stratospheric sulfate concentrations and optical properties is highly dependent on the chemistry scheme and microphysical treatment. In this work, we implemented a sophisticated gas-phase chemistry scheme (full chemistry, FC) and a 5-mode version of the Modal Aerosol Module with Prognostic Stratospheric Aerosol (MAM5-PSA) for the interactive treatment of stratospheric sulfate aerosol in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2) model to better simulate the chemistry-aerosol feedback following the Pinatubo eruption, and to compare it against a simulation using simplified chemistry (SC) and the default 4-mode version of the Modal Aerosol Module (MAM4). MAM5-PSA experiments were found to better capture the stratospheric sulfate burden from the eruption of the volcano to the end of 1992 as compared to the High-resolution Infrared Sounder (HIRS) observations, and the formation of sulfate in MAM5-PSA with FC (with an additional OH replenishment reaction) was significantly faster than in MAM4 with FC. Analyses of microphysical processes indicate that more sulfate aerosol mass was generated in total in FC experiments than in SC experiments. MAM5-PSA performs better than MAM4 in simulation of aerosol optical depth (AOD); AOD anomalies from the MAM5-PSA experiment have better agreement with observations. The simulated largest changes in global mean net radiative flux at the top of the atmosphere following the eruption were about −3 W m −2 in MAM5-PSA experiments and roughly −1.5 W m −2 in MAM4 experiments.

AEROSOL↗
DOE OSTI2025

The short-term comprehensive impact of the phase-out of global coal combustion on air pollution and climate change

With the continuous intensification of global warming, the reduction and ultimate phase-out of coal combustion is an inevitable trend in the future global energy transformation. This study comprehensively analyzed the impact of phasing out coal combustion on global emissions and concentrations of air pollutants, radiative fluxes, meteorology and climate using Community Earth System Model 2 (CESM2). The results indicate that after the global phase-out of coal combustion, there is a marked decrease in the concentrations of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ) and fine particulate matter (PM 2.5 ), with some regions experiencing a reduction of exceeding 50%. There is no significant change in global ozone (O 3 ) concentration. There are decreasing AOD and positive radiative fluxes globally in the short term, though the cloud contributes minor negative radiative fluxes. The global air temperature may increase by approximately (0.02 ± 0.15) °C on average with regional and seasonal variations, and the precipitation may potentially increase by approximately (2.7 ± 40.6) mm yr −1 globally and over 20% in equatorial regions in the short term. But combined with the decreasing trend of cloud water content in the Northern Hemisphere, it indicates a potential increase in the extremity of precipitation events. In conclusion, this study provides references for global control of air pollution, mitigation strategies of climate change, and transformation of energy structures under the objective of “carbon neutrality”, such as focusing on the negative climate impacts of exacerbating regional warming and increasing extreme precipitation resulting from the rapid reduction of aerosols in the short term.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

On-Demand Column Joining for High Energy Physics

As the Large Hadron Collider (LHC) transitions into the High-Luminosity LHC (HL-LHC) era, the volume of data to be processed is expected to increase significantly. The CMS Experiment currently utilizes various data formats, including AOD, MiniAOD, and NanoAOD, each with different levels of detail and storage requirements. This paper addresses the challenges of data duplication and storage inefficiencies in high-energy physics (HEP) analyses by proposing an on-demand column-joining solution. This approach aims to reduce data duplication by enabling the dynamic combination of NanoAOD data with auxiliary information from larger data tiers, such as MiniAOD. The proposed solution leverages Trino, a high-performance distributed SQL query engine, to perform efficient and scalable data joins. Benchmarks using CMS OpenData demonstrate the feasibility of this approach, showing that it can handle large datasets with low latency. Integration with the scikit-hep ecosystem and the coffea analysis framework is also discussed, highlighting the potential for seamless end-to-end data processing and analysis. Ongoing and future work focuses on expanding benchmarks, integrating ServiceX for data transformation, and exploring the use of native object storage solutions.

Manganelli, Nicholas [Northeastern U.]↗
DOE OSTI2026

CMS Storage Performance with RNTuple

CMS is transitioning to use ROOT’s new RNTuple data storage format for the files CMS will write in the HL-LHC era. Based on initial tests, CMS expects faster I/O and smaller files compared to the present TTree storage format. This contribution will show a comprehensive performance comparison between RNTuple and TTree I/O using CMS AOD and MiniAOD data formats as test cases for both simulation and collision data corresponding to similar data taking conditions of LHC Run 3. Quantities such as the resulting file size, the memory usage of the I/O components, and the rate of events being read from a file or written to a file will be measured. CMS’ data processing relies heavily on reading files over the local or wide area networks. The file read patterns are important because the latencies have been seen to influence the total production job times. Therefore a study on the file read patterns will be conducted by recording traces of the offset, size, and timestamp of each read request for both RNTuple and TTree. The behavior of network reads will be mimicked by reading local files where artificial latency will be added to the read requests. The effect of different latency values on the job times will be studied.

Jones, Christopher D. [Fermilab]↗