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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Rational Design of Fluorinated Electrolytes for Low Temperature Lithium‐Ion Batteries

Abstract Nonaqueous carbonate electrolytes are commonly used in commercial lithium‐ion battery (LIB). However, the sluggish Li + diffusivity and high interfacial charge transfer resistance at low temperature (LT) limit their wide adoption among geographical areas with high latitudes and altitudes. Herein, a rational design of new electrolytes is demonstrated, which can significantly improve the low temperature performance below −20 °C. This electrolyte is achieved by tailoring the chemical structure, i.e., altering the fluorination position and the degree of fluorination, of ethyl acetate solvent. It is found that fluorination adjacent to the carbonyl group or high degree of fluorination leads to a stronger electron‐withdrawing effect, resulting in low atomic charge on the carbonyl oxygen solvating sites, and thus low binding energies with Li + ions at LT. The optimal electrolyte 2,2,2‐trifluoroethyl acetate (EA‐f) shows significantly improved cycle life and C‐rate of a NMC622/graphite cell when cycled at −20 °C and −40 °C, respectively. In addition to superior LT performance, the electrolyte is nonflammable and tolerant for high voltage charging all owing to its fluorine content. This work provides guidance in designing next‐generation electrolytes to address the critical challenge at subzero temperatures.

25 ENERGY STORAGE↗
DOE OSTI2020

The scaling economics of small unit operations

We present a correlation that represents the capital costs of the components of even very small modular facilities. Conversion of distributed feedstocks (eg, associated natural gas, biomass, and carbonaceous wastes) could provide a small fraction of the liquid fuels now used for transportation in the U.S. (~6%),or nearly half of the chemical products now made from petroleum. However, those resources tend to be available at small geographically distributed sites, and they are difficult or expensive to transport to a distant processing center. Modular, and likely intensified, processes that can be numbered up promise to enable utilizing such distributed resources. Early stage economics evaluation of those processes requires cost estimates for the components, which are likely smaller in scale than can be accommodated by the 0.6 power law typically used in chemical engineering

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Machine learning to predict biomass sorghum yields under future climate scenarios

Crop yield modeling is critical in the design of national strategies for agricultural production, particularly in the context of a changing climate. Forecasting yields of bioenergy crops at fine spatial resolutions can help to evaluate near-term and long-term pathways for scaling up bio-based fuel and chemical production, and for understanding the impacts of abiotic stressors such as severe droughts and temperature extremes on potential biomass supply. In this work we used a large dataset of 28,364 Sorghum bicolor yield samples (uniquely identified by county and year of observation), environmental variables, and multiple approaches to analyze historical trends in sorghum productivity across the USA. We selected the most accurate machine learning approach (a variation of the random forest approach) to predict future trends in sorghum yields under four greenhouse gas (GHG) emission scenarios and two irrigation regimes. We identified irrigation practices, vapor pressure deficit, and time (a proxy for technological improvement) as the most important predictors of sorghum productivity. Our results showed a decreasing trend of sorghum yields over future years (on average 2.7% from 2018 to 2099), with greater decline under a high GHG emissions scenario (3.8%) and in the absence of irrigation (4.6%). Geographically, we observed the steepest predicted declines in the Great Lakes (8.2%), Upper Midwest (7.5%), and Heartland (6.7%) regions. Our study demonstrates the use of machine learning to identify environmental controllers of sorghum biomass yield and predict yields with reasonable accuracy. These results can inform the development of more realistic biomass supply projections for bioenergy if sorghum production is scaled up. (c) 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

09 BIOMASS FUELS↗
DOE OSTI2023

Designing a GIS-based supply chain for producing carinata-based sustainable aviation fuel in Georgia, USA

Carinata is a potential crop for sustainable aviation fuel (SAF) production in the southern USA. However, as a novel crop, the cost-effectiveness and environmental feasibility of carinata feedstock are unknown, and there are questions about the optimal supply chain configuration for carinata-based SAF production. This study aims to design a supply chain model for carinata-based SAF production by optimizing the location of farms and facilities (e.g. storage units, crushing mills, biorefineries) for a minimum transportation cost under a set of supply and demand conditions. An integrated mixed-integer linear programming (MILP) model was combined with geographical information system (GIS) analysis to design a spatially explicit supply chain configuration. The GIS-based network analysis considered all of the counties in Georgia to set the candidate locations of carinata farms and facilities, and determined minimum cost and emission routes between those counties and the airport using existing transportation networks and modes (e.g. road, rail and pipeline). The MILP model determined the final selection of the farms and the number of facilities and their locations over those minimum-cost routes. With this supply chain configuration, the minimum price of SAF was $\$$0.92 L –1 , which is $\$$0.44 higher than conventional aviation fuel (CAF). The associated carbon intensity of SAF was estimated at 940.7 g CO 2 e L –1 , a reduction of 66% relative to the carbon intensity of equivalent CAF. The study found that a carbon tax (or subsidy) of $\$$230.48 t CO 2 e –1 would be needed to overcome the cost differential with CAF and promote carinata-based SAF in Georgia.

09 BIOMASS FUELS↗
DOE OSTI2020

Chemical Looping of Manganese to Synthesize Ammonia at Atmospheric Pressure: Sodium as Promoter

Abstract Affordable synthetic ammonia (NH 3 ) enables the production of nearly half of the food we eat and is emerging as a renewable energy carrier. Sodium‐promoted chemical looping NH 3 synthesis at atmospheric pressure using manganese (Mn) is here demonstrated. The looping process may be advantageous when inexpensive renewable hydrogen from electrolysis is available. Avoiding the high pressure of the Haber‐Bosch process by chemical looping using earth‐abundant materials may reduce capital cost, facilitate intermittent operation, and allow operation in geographic areas where infrastructure is less sophisticated. At this early stage, the data suggest that 0.28 m 3 of a 50 % porosity solid Mn bed may suffice to produce 100 kg NH 3 per day by chemical looping, with abundant opportunities for improvement.

Aframehr, Wrya Mohammadi↗
DOE OSTI2025

Tailoring P2/P3‐Intergrowth in Manganese‐Based Layered Transition Metal Oxide Positive Electrodes via Sodium Content for Na‐Ion Batteries

High-manganese content sodium-ion positive electrodes have received heightened interest as an alternative to contemporary Li-ion chemistries due to their high abundance, low toxicity, and even geographical distribution. However, these materials typically suffer from poor capacity, unstable cycling performance, and sluggish Na + kinetics. Herein, we explore a manganese-based layered transition metal oxide (Na x N 0.25 Mn 0.75 O 2 ) and show by X-ray diffraction (XRD) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) that careful variation of the sodium content can instigate the formation of a biphasic intergrowth. This intergrown P2/P3 material offered a higher capacity than its monophasic P2 counterpart due to the P3 structure having greater low-voltage Mn 3+/4+ redox. Further, the intergrowth material offers greatly enhanced kinetics and cycling stability when compared to single-phase P3 material, due to the stabilizing nature of the P2 structure, elucidated by galvanostatic intermittent titration technique (GITT) and operando synchrotron X-ray diffraction. These results highlight the beneficial effect that the intergrowth structure has on the electrochemical performance of high-manganese content positive electrode for future sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Catalytic Graphitization of Biocarbon for Lithium‐Ion Anodes: A Minireview

Abstract The demand for electrochemical energy storage is increasing rapidly due to a combination of decreasing costs in renewable electricity, governmental policies promoting electrification, and a desire by the public to decrease CO 2 emissions. Lithium‐ion batteries are the leading form of electrochemical energy storage for electric vehicles and the electrical grid. Lithium‐ion cell anodes are mostly made of graphite, which is derived from geographically constrained, non‐renewable resources using energy‐intensive and highly polluting processes. Thus, there is a desire to innovate technologies that utilize abundant, affordable, and renewable carbonaceous materials for the sustainable production of graphite anodes under relatively mild process conditions. This review highlights novel attempts to realize the aforementioned benefits through innovative technologies that convert biocarbon resources, including lignocellulose, into high quality graphite for use in lithium‐ion anodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities

Abstract As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The impact of plant‐derived fire management prescriptions on fire‐responsive bird species

Abstract In fire‐prone regions, the occurrence of some faunal species is contingent on the presence of resources that arise through post‐fire plant succession. Through planned burning, managers can alter resource availability and aim to provide the conditions required to promote biodiversity. Understanding how species occurrence changes at different spatial and temporal scales after fire is essential to achieve this goal. However, many fire prescriptions are guided primarily by the responses of fire‐sensitive plants when setting tolerable fire intervals. This approach assumes that maintaining floristic diversity will satisfy the requirements of fauna. We surveyed bird species in two semi‐arid vegetation types across an environmental gradient in south‐eastern Australia. We conducted four surveys at each of 253 sites across a 75‐year chronosequence of time since fire and used generalized additive mixed models to examine changes in the occurrence of birds in response to time since fire. Model predictions were compared to plant‐derived fire prescriptions currently guiding fire management in the region. Time since fire was a significant predictor for 18 of 28 species modeled, in at least one vegetation type, over a gradient of 1.3° of latitude. We detected considerable variation in the responses of some species, both between vegetation types and geographically within a vegetation type. Our evaluation of plant‐derived fire prescriptions suggests that the intervals considered acceptable for maintaining floristic diversity may not be sustainable for populations of birds requiring longer unburnt vegetation, with 6 of the 12 species assessed attaining a mean occurrence probability of 20.3% by the minimum tolerable fire interval, and 57.3% by the maximum tolerable fire interval, in their respective vegetation types. Our findings highlight the potential vulnerability of fire‐responsive bird species if fire prescriptions are applied in a manner that fails to account for the slow development of habitat resources needed by some species, and the variation detected within the responses of species. This highlights the need for species‐specific data collected at an appropriate spatial scale to inform management plans.

Makdissi, Rhys↗
DOE OSTI2023

Winter connectivity and leapfrog migration in a migratory passerine

Abstract Technological advances in migratory tracking tools have revealed a remarkable diversity in migratory patterns. One such pattern is leapfrog migration, where individuals that breed further north migrate to locations further south. Here, we analyzed migration patterns in the Painted Bunting ( Passerina ciris ) using a genetic‐based approach. We started by mapping patterns of genetic variation across geographic space (called a genoscape) using 386 individuals from 25 populations across the breeding range. We then genotyped an additional 230 samples from 31 migration stopover locations and 178 samples from 16 wintering locations to map patterns of migratory connectivity. Our analyses of genetic variation across the breeding range show the existence of four genetically distinct groups within the species: Eastern, Southwestern, Louisiana, and Central groups. Subsequent assignment of migrating and wintering birds to genetic groups illustrated that birds from the Central group migrated during the fall via western Mexico or southern Texas, spent the winter from northeastern Mexico to Panama, and migrated north via the Gulf Coast of Mexico. While Louisiana birds overlapped with Central birds on their spring migratory routes along the Gulf Coast, we found that Louisiana birds had a more restricted wintering distribution in the Yucatan Peninsula and Central America. Further estimation of the straight‐line distance from the predicted breeding location to the wintering location revealed that individuals sampled at lower winter latitudes traveled to greater distances (i.e., the predicted breeding area was further north; p > .001), confirming that these species exhibit a leapfrog migration pattern. Overall, these results demonstrate the utility of a genoscape‐based approach for identifying range‐wide patterns of migratory connectivity such as leapfrog migration with a high degree of clarity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Approximation of ice phenology of Maine lakes using Aqua MODIS surface temperature data

Studies of lake ice phenology have historically relied on limited in situ data. Relatively few observations exist for ice out and fewer still for ice in, both of which are necessary to determine the temporal extent of ice cover. Satellite data provide an opportunity to better document patterns of ice phenology across landscapes and relate them to the climatological drivers behind changing ice phenology. We developed a model, the Cumulative Sum Method (CSM), that uses daytime and nighttime surface temperature observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Earth-observing Aqua satellite to approximate ice in (the onset of ice cover) and ice out from training datasets of 13 and 58 Maine lakes, respectively, during the 2002/2003 through 2017/2018 ice seasons. Ice in was signaled by reaching a threshold of cumulative negative degrees following the first day of the season below 0°C. Ice out was signaled by reaching a threshold of cumulative positive degrees following the first day of the year above 0°C. The comparison of observed and remotely sensed ice-in dates showed relative agreement with a correlation coefficient of 0.71 and a mean absolute error (MAE) of 9.8 days. Ice-out approximations had a correlation coefficient of 0.67 and an MAE of 8.8 days. Lakes smaller in surface area and nearer the Atlantic coast had the greatest error in approximation. Application of the CSM to 20 additional lakes in Maine produced a comparable ice-out MAE of 8.9 days. Ice-out model performance was weaker for the warmest years; there was a larger MAE of 12.0 days when the model was applied to the years 2019–2023 for the original 58 lakes. The development of this model, which utilizes daily satellite data, demonstrates the promise of remote sensing for quantifying ice phenology over short, temporal scales, and wider geographic regions than can be observed in situ, and allows exploration of the influence of surface temperature patterns on the process and timing of ice in and ice out.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗
DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗
DOE OSTI2023

Simulation-based characterization of the variability of earthquake risk to buildings in the near-field

Recent advancements in high performance computing platforms and computational workflow for regional-scale simulations are enabling unprecedented modeling of fault-to-structure earthquake processes. Regional simulations resolving ground motions at frequencies relevant to engineered systems are becoming computationally viable and provide a new capability to improve understanding of the geographical distribution and intensity of risk to buildings and critical infrastructure. As computational capabilities advance, it is essential to move beyond illustrative single rupture realizations for scenario earthquake events towards the development of a full suite of rupture realizations that appropriately characterize the range of risk to building systems. The work described in this article investigates the application of a suite of fault rupture realizations with the objective of assessing near-fault, site-specific seismic demand variability for building structures. A representative high-performance regional-scale computational model is utilized to execute ground motion and building response simulations based on 18 kinematic rupture realizations of an M7 strike-slip scenario earthquake. The fault rupture models for the scenario earthquake are created by systematically perturbing the hypocenter location and stochastically generating rupture parameters (slip, rise time, rake angle) to represent a breadth of ground motion intensities resulting from the spatial and temporal variabilities of an earthquake rupture process. The resulting seismic demand variability for three-story (short period) and forty-story (long period) steel moment-resisting frame buildings is characterized in terms of the median and distribution of peak inter-story drift ratio for a range of near-fault sites. The full suite of 18 fault rupture realizations and approximately 280,000 nonlinear dynamic building simulations indicate that the three-story building undergoes higher median seismic demand and significantly greater variability of demand at a given site than the forty-story building, which has important implications for the level of certainty in predicting building performance during an earthquake. The simulations performed provide deeper insight into the relationship between fault rupture parameterization and building response, which is essential information for developing a representative suite of rupture realizations for specific earthquake scenarios.

58 GEOSCIENCES↗
DOE OSTI2020

Applying cumulative effects to strategically advance large-scale ecosystem restoration

Programs restoring large terrestrial-aquatic ecosystems are expected to increase in area and number over the next decade. Factors ensuring long-term effectiveness at the program scale differ from those at the individual restoration project scale, necessitating a new synthesis. Here we contextualize hydrological, geomorphological, and biological effects of large-scale ecosystem restoration activities within a cumulative-effects paradigm. Evidence of eight modes of cumulative effects benefiting species and ecosystems was elucidated by reviewing restoration efforts in the greater Florida Everglades, Gulf Coast, lower Columbia River and estuary, Puget Sound estuary, Missouri River, northeastern coastal states, San Francisco Bay and Sacramento Delta. Additive and nonlinear cumulative effects of interacting restoration projects propagated across landscape and regional geographic scales, and throughout trophic levels, affecting population structures. Applying a cumulative-effects paradigm to planning, implementing, and evaluating large-scale restoration will avoid countervailing effects and capitalize on positive feedback, advancing evidence-based programs to recover priority species and ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mapping existing wellbore locations to compare technical risks between onshore and offshore CCS activities in Texas

Carbon dioxide capture and geologic storage (CCS; geologic sequestration) is a promising technology for reducing anthropogenic greenhouse gas emissions to the atmosphere from industrial point sources. Aspects of CCS have been investigated for over two decades, and many large- and small-scale geologic storage field demonstration projects are now underway globally. Interest in offshore CCS has been increasing in recent years (e.g., European Union, Australia, Japan, and the United States). Deep geologic storage in offshore settings is analogous to onshore CCS activities in many respects (i.e., geologic and geotechnical aspects), but is distinct from previously explored seabed sediment CO 2 storage) or deep marine dissolution). Given the large subsurface geologic storage volumes available in offshore settings, much discussion of offshore CCS is focused on the benefits and risks of such activity compared to onshore settings. Similar to onshore settings, existing (legacy) wells likely present the most direct migration pathway and largest risk of noncontainment in offshore settings. As part of current studies to evaluate geologic storage options in offshore settings along the Texas coast and greater Gulf of Mexico (GoM), mapping of the geographic distribution and ages of wells in a region containing coastal counties and extending 30 miles offshore Texas indicates that both well spatial density and well age decrease moving from onshore to offshore. Results suggest reduced risk of leakage owing to more rigorous and documented well completion and abandonment practices for these generally younger wells (although many are decades old). A result of decreased well density is that larger areas are available for leasing for CCS projects that avoid legacy wells altogether (> 1 mile from any existing well). The one-mile designation is used as an arbitrary convention, and while it is recognized that this is smaller than a typical area of review (AoR) for permitting, each site will have a different AoR radius for consideration. Finally, the combination of large subsurface storage volumes under control of a single landowner and reduced risks from legacy wells makes offshore CCS attractive in the GoM.

58 GEOSCIENCES↗
DOE OSTI2023

Relationship between isotope ratios in precipitation and stream water across watersheds of the National Ecological Observation Network

The timescales associated with precipitation moving through watersheds reveal processes that are critical to understanding many hydrologic systems. Measurements of environmental stable water isotope ratios (δ 2 H and δ 18 O) have been used as tracers to study hydrologic timescales by examining how long it takes for incoming precipitation tracers become stream discharge, yet limited measurements both spatially and temporally have bounded macroscale evaluations so far. Here in this observation driven study across North American biomes within the National Ecological Observation Network (NEON), we examined δ 18 O and δ 2 H stable water isotope in precipitation (δP) and stream water (δQ) at 26 co-located sites. With an average 54 precipitation samples and 139 stream water samples per site collected over 2014–2022, assessment of local meteoric water lines and local stream water lines showed geographic variation across North America. Taking the ratio of estimated seasonal amplitudes of δP and δQ to calculate young water fractions (F yw ), showed a Fyw range from 1% to 93% with most sites having F yw below 20%. Calculate d mean transit times (MTT) based on a gamma convolution model showed a MTT range from 0.10 to 13.2 years, with half of the sites having MTT estimates lower than 2 years. Significant correlations were found between the F yw and watershed area, longest flow length, and the longest flow length/slope. Significant correlations were found between MTT and site latitude, longitude, slope, clay fraction, temperature, precipitation magnitude, and precipitation frequency. The significant correlations between water timescale metrics and the environmental characteristics we report share some similarities with those reported in prior studies, demonstrating that these quantities are primarily driven by site or area specific factors. The analysis of isotope data presented here provides important constraints on isotope variation in North American biomes and the timescales of water movement through NEON study sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Variations in northeast Asian summer precipitation driven by the Atlantic multidecadal oscillation

By analysing a 113–year (1900–2012) observational dataset, it is shown in this work that the interdecadal fluctuation of the summer precipitation over Northeast Asia differs from that in central East Asia during the 20th century, and has experienced three interdecadal shifts in the 1920s, mid-1960s and late 1990s. That fluctuation coincides well with the multidecadal fluctuation of the sea surface temperature in the North Atlantic, known as the Atlantic Multidecadal Oscillation (AMO). The AMO affects Northeast Asia via a circumglobal teleconnection pattern extending from the North Atlantic to North America. Corresponding with the positive phase of this teleconnection pattern, a tripolar pattern emerges in the Asian–North Pacific sector, with anomalous low pressure over Northeast Asia and high pressure over Lake Baikal and the mid-latitude western North Pacific. These results suggest that the positive phase of the AMO favours the occurrence of cold vortex over Northeast Asia and anomalous highs over Lake Baikal and the mid-latitude western North Pacific in summer, which enhances the East Asian summer monsoon and southward intrusion of high-latitude cold air, and eventually increases the summer precipitation in Northeast Asia. Furthermore, initialized decadal prediction simulations using the CCSM4 model reproduce well the observed variations of the AMO and its associated atmospheric teleconnection but with slightly shifted geographic locations. The simulated anomalous Northeast Asia cold vortex and strong East Asian summer monsoon, lead to above-normal summer precipitation over Northeast Asia. The modelling results confirm that the multidecadal variability in the North Atlantic can cause the observed interdecadal variations of Northeast Asia summer precipitation. Our results suggest that to understand and predict interdecadal climate change over Northeast Asia, it is important to consider the key role of the AMO.

54 ENVIRONMENTAL SCIENCES↗