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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward Higher-order Accuracy in Self-gravitating Hydrodynamics

High-order algorithms have emerged in numerical astrophysics as a promising avenue to reduce truncation error (proportional to a power of the linear resolution Δ x ) with only a moderate increase to computational expense. Significant effort has been placed in the development of finite-volume algorithms for (magneto)hydrodynamics; however, state-of-the-art astrophysical simulations tightly couple a plenitude of physics, additionally including gravity, photon transport, cosmic-ray transport, chemistry, and/or diffusion, to name a few. Algorithms frequently operator-split this additional physics (often a first-order error in time) and/or adopt a model wherein their evaluation is limited to second-order accuracy in space. In this work, we present a fourth-order-accurate finite-volume scheme for self-gravitating hydrodynamics on a uniform Cartesian grid. The method supplies source terms for the gravitational acceleration ( ρ g ) and gravitational energy release ( ρ v · g ) associated with fourth-order-accurate solutions to the Poisson equation. Our scheme (1) guarantees the conservation of total linear momentum while (2) decreasing (in proportion to Δ x 4 ) the effects of spurious heating and/or cooling associated with truncation error in the gravity. We demonstrate expected convergence rates for the algorithm by measuring errors in test problems evolving self-gravity modified linear waves and 3D polytropic equilibria. We test robustness of the algorithm by integrating an induced “inside-out” adiabatic collapse. We also discuss a method to smoothly downgrade the solution to second-order spatial accuracy to avoid spurious overshoots near steep density and/or pressure gradients.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

On the Influence of North Pacific Sea Surface Temperature on the Arctic Winter Climate

Differences between two ensembles of Goddard Earth Observing System Chemistry-Climate Model simulations isolate the impact of North Pacific sea surface temperatures (SSTs) on the Arctic winter climate. One ensemble of extended winter season forecasts is forced by unusually high SSTs in the North Pacific, while in the second ensemble SSTs in the North Pacific are unusually low. High Low differences are consistent with a weakened Western Pacific atmospheric teleconnection pattern, and in particular, a weakening of the Aleutian low. This relative change in tropospheric circulation inhibits planetary wave propagation into the stratosphere, in turn reducing polar stratospheric temperature in mid- and late winter. The number of winters with sudden stratospheric warmings is approximately tripled in the Low ensemble as compared with the High ensemble. Enhanced North Pacific SSTs, and thus a more stable and persistent Arctic vortex, lead to a relative decrease in lower stratospheric ozone in late winter, affecting the April clear-sky UV index at Northern Hemisphere mid-latitudes.

Hurwitz, Margaret M.↗
NASA NTRS2013

Three Decades of Global Methane Sources and Sinks

Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios which differ in fossil fuel and microbial emissions to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

periodic variations↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electrocatalytic Reduction of CO 2 to CO over Ag(110) and Cu(211) Modeled by Grand-Canonical Density Functional Theory

We report the results of modeling CO 2 reduction (CO 2 R) to CO over Ag(110) and Cu(211) surfaces at different applied potentials using grand-canonical density functional theory (GC-DFT), a method specifically designed to accurately model electrochemical systems. In addition to demonstrating GC-DFT’s ability to accurately model electrochemical processes, we also compare it with the computational hydrogen electrode (CHE) approach. GC-DFT predicts that the geometries of these reacting systems strongly depend on the applied potential and the Helmholtz free energies vary nonlinearly with the applied potential, which contradicts a central assumption of the CHE approach. The CHE approach neglects the change in the number of electrons on the electrode surface at different applied potentials, which reduces its accuracy as the potential changes from the potential of zero charge. Our results further demonstrate that the grand free energies of the reaction intermediates not only depend on the value of the applied potential but also on the metal surface type, adsorption site, and adsorbate. GC-DFT’s ability to predict the effect of the applied potential on adsorbate geometry enables it to evaluate different possible reaction mechanisms at different applied potentials. For instance, GC-DFT predicts that the first step of CO2R likely switches from proton-coupled electron transfer to sequential electron transfer and then proton transfer at more reducing potentials, a result that cannot be determined by the CHE because it assumes that all electron transfers are coupled to proton transfers and neglects the effect of the applied potential on the adsorbate geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A U.S.-China coal power transition and the global 1.5 °C pathway

As the world seeks to increase ambition rapidly to limit global warming to 1.5 °C, joint leadership from the world's largest greenhouse gas (GHG) emitters—the United States (U.S.) and China—will be critical to deliver significant emissions reductions from their own countries as well as to catalyze increased international action. After a period of uncertainty in international climate policy, these countries now both have current leadership that supports ambitious climate action. In this context, a feasible, high-impact, and potentially globally catalytic agreement by the U.S. and China to transition away from coal to clean energy would be a major contribution toward this global effort. We undertake a plant-by-plant assessment in the power sector to identify practical coal retirement pathways for each country that are in line with national priorities and the global 1.5 °C target. Our plant-by-plant analysis shows that the 1.5 °C-compatible pathways may result in an average retirement age of 47 years for the U.S. coal plants and 22 years for Chinese coal plants, raising important questions of how to compare broader economic, employment, and social impacts. We also demonstrate that such pathways would also lead to significant emissions reductions, lowering overall global energy-related CO 2 emissions by about 9% in 2030 relative to 2020. A catalytic effect from the possibility of other countries taking compatible actions is estimated to reduce global emissions by 5.1 Gt CO 2 in 2030 and by 10.1 Gt CO 2 in 2045.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Molecular Imaging Reveals Two Distinct Mixing States of PM 2.5 Particles Sampled in a Typical Beijing Winter Pollution Case

Mixing states of aerosol particles are crucial for understanding the role of aerosols in influencing air quality and climate. However, a fundamental understanding of the complex mixing states is still lacking because most traditional analysis techniques only reveal bulk chemical and physical properties with limited surface and 3-D information. In this research, 3-D molecular imaging enabled by ToF-SIMS was used to elucidate the mixing states of PM 2.5 samples obtained from a typical Beijing winter haze event. In light pollution cases, a thin organic layer covers separated inorganic particles, while in serious pollution cases, ion exchange and an organic-inorganic mixing surface on large-area particles were observed. Finally, the new results provide key 3-D molecular information of mixing states, which is highly desirable for reducing uncertainty and bias in representing aerosol-cloud interactions in current Earth System Models, and improving the understanding of aerosols on air quality and human health.

3-D molecular imaging↗
DOE OSTI2020

Source of 12 C in Calvin–Benson cycle intermediates and isoprene emitted from plant leaves fed with 13 CO 2

Feeding 14 CO 2 was crucial to uncovering the path of carbon in photosynthesis. Feeding 13 CO 2 to photosynthesizing leaves emitting isoprene has been used to develop hypotheses about the sources of carbon for the methylerythritol 4-phosphate pathway, which makes the precursors for terpene synthesis in chloroplasts and bacteria. Both photosynthesis and isoprene studies found that products label very quickly (<10 min) up to 80–90% but the last 10–20% of labeling requires hours indicating a source of 12 C during photosynthesis and isoprene emission. Furthermore, studies with isoprene showed that the proportion of slow label could vary significantly. This was interpreted as a variable contribution of carbon from sources other than the Calvin–Benson cycle (CBC) feeding the methylerythritol 4-phosphate pathway. Here, we measured the degree of label in isoprene and photosynthetic metabolites 20 min after beginning to feed 13 CO 2 . Isoprene labeling was the same as labeling of photosynthesis intermediates. High temperature reduced the label in isoprene and photosynthesis intermediates by the same amount indicating no role for alternative carbon sources for isoprene. A model assuming glucose, fructose, and/or sucrose reenters the CBC as ribulose 5-phosphate through a cytosolic shunt involving glucose 6-phosphate dehydrogenase was consistent with the observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Direct numerical simulation of turbulent H2-O2 combustion using reduced chemistry

Results of direct numerical simulations of hydrogen-oxygen combustion using a partial-equilibrium chemistry scheme in constant density, decaying, isotropic turbulence are reported. The simulations qualitatively reproduce many features of experimental results, such as superequilibrium radical species mole fractions, with temperature and major species mole fractions closer to chemical equilibrium. It was also observed that the peak reaction rates occur in narrow zones where the stoichiometric surface intersects regions of high scalar dissipation, as might be expected for combustion conditions close to chemical equilibrium. Another finding was that high OH mole fraction correspond more closely to the stoichiometric surface than to areas of high reaction rate for conditions of the simulations. Simulation results were compared to predictions of the Conditional Moment Closure model. This model was found to give good results for all quantities of interest when the conditionally averaged scalar dissipation was used in the prediction. When the nonconditioned average dissipation was used, the predictions compared well to the simulations for most of the species and temperature, but not for the reaction rate. The comparison would be expected to improve for higher Reynolds number flows, however.

Montgomery, Christopher J.↗
DOE OSTI2026

Ensemble Effects on Hydroxide Bond Dissociation Free Energies in Polyoxovanadate Clusters

Understanding structure-property relationships is foundational to numerous modern chemistries, such as proton-coupled electron transfer (PCET). However, an experimentally measured property is the result of the behavior from an ensemble of molecules. Neglecting ensemble effects, especially under complex chemical environments, may obfuscate these relationships and lead to discrepancies between theory and experiment. In this work, we demonstrate the impact of configurational entropy and local chemical environments on hydroxide bond dissociation free energies [BDFE- (O−H)] for a set of polyoxovanadate nanoclusters, at ambient conditions. The O−H bond strengths are investigated via density functional theory (DFT) coupled with statistical thermodynamic analysis and bilinear modeling, and compared with previous experimental results on the same systems, namely electrochemical solutions of: [V 6 O 13−x (OH) x (TRIOL R ) 2 ] −2 (x = 2, 4, 6; R = NO 2 , Me) and [V 6 O 11−x (OMe) 2 (OH) x (TRIOL NO 2 ) 2 ] −2 (x = 2, 4). Interestingly, we find that ensemble effects, even at room temperature, can account for a significant portion of the BDFE(O−H) trend with the degree of reduction via H atom binding, which cannot be fully captured by single-structure, static DFT calculations. Moreover, we find that the ensemble effects may be replicated statistically, requiring only enumeration of energetically accessible H-binding sites. With the ensemble effects resolved, we present a simple bilinear model to reconcile remaining biases between experiment and ensemble-informed theory, which corelate with clusterspecific electronic environment differences. The bilinear model achieves outstanding accuracy vs experiments with a root-mean squared error of 0.4 kcal/mol. Finally, based on the physicochemical characteristics of hydrogen interaction with polyoxometalates, we present a simple methodology that captures the BDFE(O−H) trend while dramatically reducing required DFT calculations by 98% and achieving accuracy within 1 kcal/mol. Overall, this work elucidates the roles and structural origins of configurational entropy and chemical effects on polyoxometalate hydroxide bond energies, with potential applicability to various atomically precise metal oxide systems. Importantly, it introduces models for rapid and highly accurate property calculations in connection with experiments.

Cluster chemistry↗
DOE OSTI2024

Resistance of Boron Nitride Nanotubes to Radiation-Induced Oxidation

We present unprecedented results on the damage thresholds and pathways for boron nitride nanotubes (BNNT) under the influence of energetic electrons in an oxidative gas environment, using an environmental aberration-corrected electron microscope over a range of oxygen pressures. We observe a damage cascade process that resists damage until a higher electron dose, compared with carbon nanotubes, initiating at defect-free BNNT sidewalls and proceeding through the conversion from crystalline nanotubes to amorphous boron nitride (BN), resisting oxidation throughout. We compare with prior results on the oxidation of carbon nanotubes and present a model that attributes the onset of damage in both cases to a physisorbed oxygen layer that reduces the threshold for damage onset. Surprisingly, increased temperatures offer protection against damage, as do electron dose rates that significantly exceed the oxygen dose rates, and our model attributes both effects to a physisorbed oxygen population.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Analytical ab initio hessian from a deep learning potential for transition state optimization

Identifying transition states—saddle points on the potential energy surface connecting reactant and product minima—is central to predicting kinetic barriers and understanding chemical reaction mechanisms. In this work, we train a fully differentiable equivariant neural network potential, NewtonNet, on thousands of organic reactions and derive the analytical Hessians. By reducing the computational cost by several orders of magnitude relative to the density functional theory (DFT) ab initio source, we can afford to use the learned Hessians at every step for the saddle point optimizations. We show that the full machine learned (ML) Hessian robustly finds the transition states of 240 unseen organic reactions, even when the quality of the initial guess structures are degraded, while reducing the number of optimization steps to convergence by 2–3× compared to the quasi-Newton DFT and ML methods. All data generation, NewtonNet model, and ML transition state finding methods are available in an automated workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Effects of Rhenium Addition on the Temporal Evolution of the Nanostructure and Chemistry of a Model Ni-Cr-Al Superalloy: Analysis of the Coarsening Behavior - 2

The temporal evolution of the nanostructure and chemistry of a model Ni-8.5 at.% Cr-10 at.% Al alloy with the addition of 2 at.% Re was studied using transmission electron microscopy and atom-probe tomography in order to measure the number density and mean radius of the y' (LIZ) precipitates and the chemistry of the y'-precipitates and the y (fcc)-matrix. In this article, the coarsening behavior of the y'-precipitates is discussed in detail and compared with the Umantsev-Olson model for multi-component alloys. In addition, the experimental results are evaluated with PrecipiCalc(TradeMark) simulations. The results show that the diffusivities of the solute elements play a major role in the coarsening behavior of the y'-precipitates and that the addition of Re retards the coarsening kinetics and stabilizes the spheroidal morphology of the precipitates by reducing the interfacial energy.

Yoon, Kevin E.↗
NASA NTRS2020

The Impacts of Fossil Fuel Emission Uncertainties and Accounting for 3-D Chemical CO2 Production on Inverse Natural Carbon Flux Estimates from Satellite and In Situ Data

Atmospheric carbon dioxide (CO2) inversions for estimating natural carbon fluxes typically do not allow for adjustment of fossil fuel CO2 emissions, despite significant uncertainties in emission inventories and inadequacies in the specification of international bunker emissions in inversions. Also, most inversions place CO2 release from fossil fuel combustion and biospheric sources entirely at the surface. However, a non-negligible portion of the emissions actually occurs in the form of reduced carbon species, which are eventually oxidized to CO2 downwind. Omission of this ‘chemical pump’ can result in a significant redistribution of the inferred total carbon fluxes among regions. We assess the impacts of different prescriptions of fossil fuel emissions and accounting for the chemical pump on flux estimation, with a novel aspect of conducting both satellite CO2 observation-based and surface in situ-based inversions. We apply 3-D carbon monoxide (CO) loss rates archived from a state-of-the-art GEOS chemistry and climate model simulation in a forward transport model run to simulate the distribution of CO2 originating from oxidation of carbon species. We also subtract amounts from the prior surface CO2 fluxes that are actually emitted in the form of fossil and biospheric CO, methane, and nonmethane volatile organic compounds (VOCs). We find that the posterior large-scale fluxes are generally insensitive to the finer-scale spatial differences between the ODIAC and CDIAC fossil fuel CO2 gridded datasets and assumptions about international bunker emissions. However, accounting for 3-D chemical CO2 production and the surface correction shifts the global carbon sink, e.g., from land to ocean and from the tropics to the north, with a magnitude and even direction that depend on assumptions about the surface correction. A GOSAT satellite-based inversion is more sensitive to the chemical pump than one using in situ observations, exhibiting substantial flux impacts of 0.28, 0.53, and -0.47 Pg C yr(exp -1) over tropical land, global land, and oceans, due to differences in the horizontal and vertical sampling of the wo observation types. Overall, the biases from neglecting the chemical pump appear to be minor relative to the flux estimate uncertainties and the differences between the in situ and GOSAT inversions, but their relative importance will grow in the future as observational coverage further increases and satellite retrieval biases decrease.

James S Wang↗
DOE OSTI2025

A comprehensive approach for elucidating the interplay between 4f n +1 and 4f n 5d 1 configurations in Ln 2+ complexes

Lanthanides (Ln) are typically found in the +3 oxidation state. However, in recent decades, their chemistry has been expanded to include the less stable +2 oxidation state across the entire series except promethium (Pm), facilitated by the coordination of ligands such as trimethylsilylcyclopentadienyl, C 5 H 4 SiMe 3 (Cp'). The [LnCp' 3 ] complexes have been the workhorse for the synthesis and theoretical study of the fundamental aspects of divalent lanthanide chemistry, where experimental and computational evidence have suggested the existence of different ground state (GS) configurations, 4f n+1 or 4f n 5d 1 , depending on the specific metal. Standard reduction potentials and 4f n+1 to 4f n 5d 1 promotion energies have been two factors usually considered to rationalize the occurrence of these variable GS configurations, however the driving force behind this phenomenon is still not clear. In this work we present a comprehensive theoretical approach to shed light on this matter using the [LnCp 3 ] - model systems. We begin by calculating 4f n+1 to 4f n 5d 1 promotion energies and successfully correlate them with existing experimental data. Furthermore, we analyze how changes in the GS charge distribution between the Ln ions, LnCp 3 and the reduced [LnCp 3 ] - complexes (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) correlate with experimental trends in redox potentials and the calculated promotion energies. For this purpose, a comprehensive theoretical work that includes relativistic ligand field density functional theory (LFDFT) and relativistic ab initio wavefunction methods was performed. This study will help the rational design of suitable environments to tune the different GS configurations as well as modulating the spectroscopic properties of new Ln 2+ complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2020

The Global Methane Budget 2000–2017

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4/yr (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4/yr or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4/yr or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4/yr larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4/yr larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4/yr, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30° N) compared to mid-latitudes (∼ 30 %, 30–60° N) and high northern latitudes (∼ 4 %, 60–90° N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4/yr lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4/yr by 8 Tg CH4/yr, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.

methane budget↗
NASA NTRS2014

Diurnal Variations of Stratospheric Ozone Measured by Ground-Based Microwave Remote Sensing at the Mauna Loa NDACC Site: Measurement Validation and GEOSCCM Model Comparison

There is presently renewed interest in diurnal variations of stratospheric and mesospheric ozone for the purpose of supporting homogenization of records of various ozone measurements that are limited by the technique employed to being made at certain times of day. We have made such measurements for 19 years using a passive microwave remote sensing technique at the Mauna Loa Observatory (MLO) in Hawaii, which is a primary station in the Network for Detection of Atmospheric Composition Change (NDACC). We have recently reprocessed these data with hourly time resolution to study diurnal variations. We inspected differences between pairs of the ozone spectra (e.g., day and night) from which the ozone profiles are derived to determine the extent to which they may be contaminated by diurnally varying systematic instrumental or measurement effects. These are small, and we have reduced them further by selecting data that meet certain criteria that we established. We have calculated differences between profiles measured at different times: morning-night, afternoon-night, and morning-afternoon and have intercompared these with like profiles derived from the Aura Microwave Limb Sounder (Aura-MLS), the Upper Atmosphere Research Satellite Microwave Limb Sounder (UARS-MLS),t he Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES), and Solar Backscatter Ultraviolet version 2 (SBUV2) measurements. Differences between averages of coincident profiles are typically less than 1.5 percent of typical nighttime values over most of the covered altitude range with some exceptions. We calculated averages of ozone values for each hour from the Mauna Loa microwave data, and normalized these to the average for the first hour after midnight for comparison with corresponding values calculated with the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). We found that the measurements and model output mostly agree to better than 1.5 percent of the midnight value, with one noteworthy exception: The measured morning-night values are significantly (2-3 percent) higher than the modeled ones from 3.2 to 1.8 hPa (approximately 39-43 km), and there is evidence that the measured values are increasing compared to the modeled values before sunrise in this region.

GEOSCCM model comparison↗
NASA NTRS1991

Computerized reduction of elementary reaction sets for combustion modeling

If the entire set of elementary reactions is to be solved in the modeling of chemistry in computational fluid dynamics, a set of stiff ordinary differential equations must be integrated. Some of the reactions take place at very high rates, requiring short time steps, while others take place more slowly and make little progress in the short time step integration. The goal is to develop a procedure to automatically obtain sets of finite rate equations, consistent with a partial equilibrium assumptions, from an elementary set appropriate to local conditions. The possibility of computerized reaction reduction was demonstrated. However, the ability to use the reduced reaction set depends on the ability of the CFD approach in incorporate partial equilibrium calculations into the computer code. Therefore, the results should be tested on a code with partial equilibrium capability.

Wikstrom, Carl V.↗