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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrating crystallographic and computational approaches to carbon-capture materials for the mitigation of climate change

Here, this article presents an overview of the current state of the art in the structure determination of microporous carbon-capture materials, as discussed at the recent NIST workshop “Integrating Crystallographic and Computational Approaches to Carbon-Capture Materials for the Mitigation of Climate Change”. The continual rise in anthropogenic CO 2 concentration and its effect on climate change call for the implementation of carbon capture technologies to reduce the CO 2 concentration in the atmosphere. Porous solids, including metal–organic frameworks (MOFs), are feasible candidates for gas capture and storage applications. However, determining the structure of these materials represents a significant obstacle in their development into advanced sorbents. The existing difficulties can be overcome by integrating crystallographic methods and theoretical modeling. The workshop gathered experimentalists and theorists from academia, government, and industry to review this field and identify approaches, including collaborative opportunities, required to develop tools for rapid determination of the structures of porous solid sorbents and the effect of structure on the carbon capture performance. We highlight the findings of that workshop, especially in the need for reference materials, standardized procedures and reporting of sorbent activation and adsorption measurements, standardized reporting of theoretical calculations, and round-robin structure determination.

36 MATERIALS SCIENCE↗
DOE OSTI2024

We need a solid scientific basis for nature-based climate solutions in the United States

Nature-based climate solutions (NbCS) have courted both enthusiastic support and considerable controversy. Defined as deliberate human actions that manipulate ecosystems to improve the planet’s greenhouse gas balance, NbCS provoke disagreement, in large part because their implementation has so far outpaced a science-based understanding of their long-term climate mitigation potential.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Albedo of crops as a nature-based climate solution to global warming

Abstract Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming. Still, there is little understanding about how distinctive features of a cropping system may be responsible for elevated albedo and consequently for the cooling potential of cultivated lands. To address this pressing issue, we conducted seasonal measurements of surface reflectivity during five growing seasons on annual crops of corn-soybean–winter wheat ( Zea mays L.- Glycine max L. Merrill - Triticum aestivum L. ; CSW) rotations at three agronomic intensities, a monoculture of perennial switchgrass ( Panicum virgatum L. ), and perennial polycultures of early successional and restored prairie grasslands. 
We found that crop-species, agronomic intensity, seasonality, and plant phenology had significant effects on albedo. The mean±SD albedo was highest in perennial crops of switchgrass (0.179±0.04), intermediate in early successional crops (0.170±0.04), and lowest in a reduced input corn systems with cover crops (0.154±0.02). The strongest cooling potentials were found in soybean (-0.450 kg CO 2 e m -2 yr -1 ) and switchgrass (-0.367 kg CO 2 e m -2 yr -1 ), with up to -0.265 kg CO 2 e m -2 yr -1 of localized climate cooling annually provided by different agroecosystems. We also demonstrated how diverse ecosystems, leaf canopy, and agronomic practices can affect surface reflectivity and provide another potential nature-based solution for reducing global warming at localized scales.

Lei, Cheyenne (ORCID:0000000272746309)↗
DOE OSTI2024

Provincial-scale assessment of direct air capture to meet China’s climate neutrality goal under limited bioenergy supply

China has large, estimated potential for direct air carbon capture and storage (DACCS) but its deployment locations and impacts at the subnational scale remain unclear. This is largely because higher spatial resolution studies on carbon dioxide removal (CDR) in China have focused mainly on bioenergy with carbon capture and storage. This study uses a spatially detailed integrated energy-economy-climate model to evaluate DACCS for 31 provinces in China as the country pursues its goal of climate neutrality by 2060. We find that DACCS could expand China’s negative emissions capacity, particularly under sustainability-minded limits on bioenergy supply that are informed by bottom-up studies. But providing low-carbon electricity for multiple GtCO 2 yr -1 DACCS may require over 600 GW of additional wind and solar capacity nationwide and comprise up to 30% of electricity demand in China’s northern provinces. Investment requirements for DACCS range from 330 to 530 billion dollars by 2060 but could be repaid manyfold in the form of avoided mitigation costs, which DACCS deployment could reduce by up to $6 trillion over the same period. Enhanced efforts to lower residual CO 2 emissions that must be offset with CDR under a net-zero paradigm reduce but do not eliminate the use of DACCS for mitigation. For decision-makers and the energy-economy models guiding them, our results highlight the value of expanding beyond the current reliance on biomass for negative emissions in China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Predicted range expansion of Prostephanus truncatus (Coleoptera: Bostrichidae) under projected climate change scenarios

Abstract The larger grain borer (Prostephanus truncatus [Horn] [Coleoptera: Bostrichidae]) is a wood-boring insect native to Central America and adapted to stored maize and cassava. It was accidentally introduced to Tanzania and became a pest across central Africa. Unlike many grain pests, P. truncatus populations can establish and move within forests. Consequently, novel infestations can occur without human influence. The objectives of our study were to (i) develop an updated current suitability projection for P. truncatus, (ii) assess its potential future distribution under different climate change scenarios, and (iii) identify climate variables that best inform the model. We used WALLACE and MaxEnt to predict potential global distribution by incorporating bioclimatic variables and occurrence records. Future models were projected for 2050 and 2070 with Representative Concentration Pathways (RCPs) 2.6 (low change) and 8.5 (high change). Distribution was most limited by high precipitation and cold temperatures. Globally, highly suitable areas (> 75%) primarily occurred along coastal and equatorial regions with novel areas in northern South America, India, southeastern Asia, Indonesia, and the Philippines, totaling 7% under current conditions. Highly suitable areas at RCPs 2.6 and 8.5 are estimated to increase to 12% and 15%, respectively, by 2050 and increase to 19% in 2070 under RCP 8.5. Centroids of highly suitable areas show distribution centers moving more inshore and away from the equator. Notably, the result is a range expansion, not a shift. Results can be used to decrease biosecurity risks through more spatially explicit and timely surveillance programs for targeting the exclusion of this pest.

Entomology↗
DOE OSTI2024

Tropical Indian Ocean drives Hadley circulation change in a warming climate

ABSTRACT The weakening and poleward expansion of the Hadley circulation (HC) are considered robust responses of atmospheric meridional circulation to anthropogenic warming. Climate impacts arising from these changes enhance drought conditions and reduce food production in the affected regions. Therefore, understanding the mechanisms of HC changes is critical to anticipating the resultant climate risks. First, we demonstrate that robust future HC changes in boreal winter, and the uncertainty in their future projections, are both largely related to sea surface temperature (SST) warming. Next, we investigate the impact of anthropogenic regional ocean warming on the future HC. Accordingly, we conduct a large ensemble of individual ocean basin perturbation experiments at 1.5°C, 2°C, and 3°C warming thresholds (as in the Paris Agreement). These experiments highlight (i) the leading role of tropical Indian Ocean warming in HC changes and (ii) inter-model differences in tropical Pacific warming as a source of uncertainty in HC projections.

Sun, Yong (ORCID:0000000210876060)↗
DOE OSTI2024

Measured Long-Term Solar Irradiance for Climate Studies

Solar radiation is primarily measured using high-quality radiometers (e.g., pyranometers and pyrheliometers). These instruments need to be calibrated regularly (every two years at a minimum). They are also susceptible to various sources of uncertainties. Therefore, rigorous data quality assessment is required to obtain high-confidence data from these radiometers. This is especially true when the data is used to understand climatic trends and/or extreme weather events. In this study, we attempted to create a continuous and reliable dataset by correcting the underlying data which we believe contains bias due to reference pyranometers swap procedures. These biases can be significant which can be up to two percentage points thereby influencing the interpretation of climate changes and/or extreme events. This study elaborates on the biases and methods to correct those biases.

data integrity↗
DOE OSTI2025

Scalable Multi-Facility Workflows for Artificial Intelligence Applications in Climate Research

Earth observation satellites and earth system models are sources of vast, multi-modal datasets that are invaluable for advancing climate and environmental research. However, their scale and complexity pose significant challenges for processing and analysis. In this paper we discuss our experiences in developing and using a scientific research application using an automated multi-facility workflow that orchestrates data collection, preprocessing, artificial intelligence (AI) inferencing, and data movement across diverse computational resources, leveraging the Advanced Computing Ecosystem Testbed at the Oak Ridge Leadership Computing Facility (OLCF). We demonstrate that our workflow can be seamlessly integrated and orchestrated across research facilities managed by different federal agencies, thus allowing users to extract new scientific insights from climate datasets. The experimental results indicate that the multi-facility workflow significantly reduces processing time, enhances scalability, and maintains high efficiency across varying workloads. Notably, our workflow processes 12,000 high-resolution satellite images in just 44 seconds using 80 workers distributed across 10 nodes on the OLCF systems. Such high throughput is essential for dynamic tokenization and sharding of petascale satellite data for distributed AI model training and inferencing at scale across thousands of GPUs.

Kurihana, Takuya [ORNL] (ORCID:0000000156698565)↗
DOE OSTI2024

Data‐driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Summary Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops. Using 727 maize ( Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Kusmec, Aaron↗
DOE OSTI2026

Evolutionary constraints and climate variability jointly shape starch–sugar balance in woody plants

Nonstructural carbohydrates (NSC) buffer plants against carbon imbalances, yet their partitioning between storage and soluble pools remains elusive at global scales. Here, we compiled a dataset of starch to soluble sugar ratio (St : Su) for 308 woody species across 220 sites world-wide and introduce a dimensionless index that integrates storage and demand while minimizing methodological artifacts. St : Su was strongly associated with growth, identifying it as a key axis of carbon allocation. Foliage consistently exhibited lower St : Su than lignified organs, reflecting a division between transient and conservative pools. Conifers accumulated more starch in foliage but less in stems relative to angiosperms, while leaf habits and mycorrhizal associations further modulated organ-specific strategies. Contrary to expectation, foliar and root St : Su varied little among biomes, but stems exhibited higher ratios in tropical rainforests than in boreal or arid regions, reflecting differences in species composition and adaptive storage under disturbance. Phylogeny constrained stem storage, whereas climatic variability, rather than mean conditions, dominated allocation in leaves and roots. These findings establish St : Su as a robust functional trait linking allocation strategies, growth, and resilience, which can be used to improve vegetation model prediction of forest productivity and mortality under climate variability.

Li, Weibin [Lanzhou Univ. (China)] (ORCID:00000001↗
DOE OSTI2026

Energy Impact of Radiative Cooling Paints in Warehouses Under Various United States Climates

Although radiative cooling research is widely found in the literature, no comprehensive study has yet been conducted on the impact of novel radiant cooling (>0.91 reflectance) on the energy efficiency of warehouses. Here, in this work, we develop three building models based on a Department of Energy prototype warehouse model using trnsys, representing a typical warehouse with a black roof, a typical warehouse with a white roof, and a warehouse with novel radiative cooling (RC) paint on its roof. These models are run for 15 different cities, each representative of a different ASHRAE climate zone, to better understand the impact of RC in many different climates. It was found that an RC-coated roof in a warehouse could reduce the building's annual heating, ventilation, and air conditioning (HVAC) loads by up to 14.11 kWh/m 2 of the roof area compared to a black roof, resulting in a maximum reduction in energy costs of 0.55 $\$$/m 2 or $\$$2646/year for a large 4835 m 2 warehouse. Similarly, replacing the typical white roof coating with an RC coating could reduce the warehouse's energy consumption by up to 8.17 kWh/ m 2 of roof area, thus reducing energy costs by as much as 0.29 $\$$/m 2 or $\$$1386/year for a 4835 m 2 warehouse. In addition, applying RC paint to an unconditioned warehouse could reduce the building's ASHRAE Standard 55 indoor temperature exceedance by up to 1330 h/year compared to a black roof and up to 532 h/year compared to a white roof.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Climate-carbon feedback tradeoff between Arctic and alpine permafrost under warming

Whether greenhouse gas (GHG) emissions from permafrost will trigger positive climate feedbacks under warming remains unknown. Here, we synthesized the response of growing season carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions to experimentally manipulated warming of ~2°C for permafrost in alpine and Arctic regions. Warming weakened the GHG sink of alpine permafrost, thereby increasing (13%) its global warming potential, but strengthened the GHG sink of Arctic permafrost and decreased (-10%) its global warming potential. When warming caused drying of alpine permafrost soils, the CO2 sink weakened but the CH4 sink increased. In contrast, warming of relatively wet Arctic permafrost increased the CO2 sink and CH4 source. Warming led to much stronger increases of the N2O source in alpine than Arctic permafrost. Although keeping additional warming below 2°C in permafrost regions can avoid the positive permafrost-climate feedback, measures are needed to maintain fragile carbon sink of alpine permafrost ecosystems.

Bao, Tao↗
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↗
DOE OSTI2025

Pan-Pacific low-frequency modes of sea level and climate variability

Tide gauges provide a long observational record that can inform the nature of satellite-era basin-scale sea level trends. However, common signals must be extracted from geographically sparse records. Here, by applying low-frequency component analysis (LFCA) to tide gauge records and surface climate reconstructions, we isolate three coherent modes of Pacific Ocean variability that we ascribe to: a secular, greenhouse gas–driven climate change (LFC1); a nonlinear mode of variability with a reversal around 1980, potentially linked to aerosols (LFC2); and the Interdecadal Pacific Oscillation (LFC3). Although sea level trend patterns reflect the superimposed contribution of all modes, satellite-era trends are dominated by an increasing phase of LFC2: They are thus potentially unrepresentative of both longer-term historical patterns and those expected in the future.

Science & Technology - Other Topics↗
DOE OSTI2025

Thermal acclimation of stem respiration implies a weaker carbon-climate feedback

The efflux of carbon dioxide (CO2) from woody stems, a proxy for stem respiration, is a critical carbon flux from ecosystems to the atmosphere, which increases with temperature on short timescales. However, plants acclimate their respiratory response to temperature on longer timescales, potentially weakening the carbon-climate feedback. The magnitude of this acclimation is uncertain despite its importance for predicting future climate change. We develop an optimality-based theory dynamically linking stem respiration with leaf water supply to predict its thermal acclimation. We show that the theory accurately reproduces observations of spatial and seasonal change. We estimate the global value for current annual stem CO2 efflux as 27.4 ± 5.9 PgC. By 2100, incorporating thermal acclimation reduces projected stem respiration without considering acclimation by 24 to 46%, thus reducing land ecosystem carbon emissions.

Zhang, Han↗
DOE OSTI2025

Building hypotheses to understand the synergistic effects of heat and pollution exposure in a changing climate

The increasing intensity, frequency, and duration of extreme weather events due to climate change poses a broad range of health risks, and the synergistic effects of extreme temperature co-occurring with other hazardous exposures such as air pollution may result in higher risks of all-cause mortality and cardiovascular and respiratory morbidity than exposure to either event alone. There are a number of hypothesized mechanisms for this interaction effect, including increased susceptibility to heat effects on chronic conditions affected by air pollution exposure, exacerbation of pollution effects due to temperature-induced stress, and shared pathophysiological pathways (e.g., systemic inflammation), but specific physiological mechanisms are not well understood. In this editorial, the authors discuss this aspect of a recently published study examining ambient formaldehyde combined with high temperature exposure and respiratory disease admissions among children. Here, the observation that the health effects of pollutants such as formaldehyde are amplified following periods of high temperature can help inform risk warning systems even without knowledge of the underlying physiological mechanisms, but a deeper biological understanding of the interaction effects of heat and ambient air pollution may better inform interventions. This is even more important in view of increases in both extreme temperature and pollution events tied to climate change.

Chambliss, Sarah [University of Texas at Austin, T↗
DOE OSTI2025

ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

Sparse observations and coarse-resolution climate models limit effective regional decision-making, underscoring the need for robust downscaling. However, existing AI methods struggle with generalization across variables and geographies and are constrained by the quadratic complexity of Vision Transformer (ViT) self-attention. We introduce ORBIT-2, a scalable foundation model for global, hyper-resolution climate downscaling. ORBIT-2 incorporates two key innovations: (1) Residual Slim ViT (Reslim), a lightweight architecture with residual learning and Bayesian regularization for efficient, robust prediction; and (2) TILES, a tile-wise sequence scaling algorithm that reduces self-attention complexity from quadratic to linear, enabling long-sequence processing and massive parallelism. ORBIT-2 scales to 10 billion parameters across 65,536 GPUs, achieving up to 4.1 ExaFLOPS sustained throughput and 74–98% strong scaling efficiency. It supports downscaling to 0.9 km global resolution and processes sequences up to 4.2 billion tokens. On 7 km resolution benchmarks, ORBIT-2 achieves high accuracy with R2 scores in range of 0.98–0.99 against observation data.

Wang, Xiao [ORNL] (ORCID:0000000165451943)↗
DOE OSTI2024

Physiological Responses of C4 Perennial Bioenergy Grasses to Climate Change: Causes, Consequences, and Constraints

C 4 perennial bioenergy grasses are an economically and ecologically important group whose responses to climate change will be important to the future bioeconomy. These grasses are highly productive and frequently possess large geographic ranges and broad environmental tolerances, which may contribute to the evolution of ecotypes that differ in physiological acclimation capacity and the evolution of distinct functional strategies. C 4 perennial bioenergy grasses are predicted to thrive under climate change—C 4 photosynthesis likely evolved to enhance photosynthetic efficiency under stressful conditions of low [CO 2 ], high temperature, and drought—although few studies have examined how these species will respond to combined stresses or to extremes of temperature and precipitation. Important targets for C 4 perennial bioenergy production in a changing world, such as sustainability and resilience, can benefit from combining knowledge of C 4 physiology with recent advances in crop improvement, especially genomic selection.

Plant Sciences↗