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PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗

Spatial Distributions of Metal Atoms During Carbon SWNTs Formation: Measurements and Modelling

Experiments and modelling have been undertaken to clarify the role of metal catalysts during single-wall carbon nanotube formation. For instance, we wonder whether the metal catalyst is active as an atom, a cluster, a liquid or solid nanoparticle [1]. A reactor has been developed for synthesis by continuous CO2-laser vaporisation of a carbon-nickel-cobalt target in laminar helium flow. The laser induced fluorescence technique [2] is applied for local probing of gaseous Ni, Co and CZ species throughout the hot carbon flow of the target heated up to 3500 K. A rapid depletion of C2 in contrast to the spatial extent of metal atoms is observed in the plume (Fig. 1). This asserts that C2 condenses earlier than Ni and Co atoms.[3, 4]. The depletion is even faster when catalysts are present. It may indicate that an interaction between metal atoms and carbon dimers takes place in the gas as soon as they are expelled from the target surface. Two methods of modelling are used: a spatially I-D calculation developed originally for the arc process [5], and a zero-D time dependent calculation, solving the chemical kinetics along the streamlines [6]. The latter includes Ni cluster formation. The peak of C2 density is calculated close to the target surface where the temperature is the highest. In the hot region, C; is dominant. As the carbon products move away from the target and mix with the ambient helium, they recombine into larger clusters, as demonstrated by the peak of C5 density around 1 mm. The profile of Ni-atom density compares fairly well with the measured one (Fig. 2). The early increase is due to the drop of temperature, and the final decrease beyond 6 mm results from Ni cluster formation at the eutectic temperature (approx.1600 K).

Cau, M.↗

The satellite power system - Assessment of the environmental impact on middle atmosphere composition and on climate

Numerical models were developed to calculate the total deposition of watervapor, hydrogen, CO2, CO, SO2, and NO in the middle atmosphere from operation of heavy lift launch vehicles (HLLV) used to build a satellite solar power system (SPS). The effects of the contaminants were examined for their effects on the upper atmosphere. One- and two-dimensional models were formulated for the photochemistry of the upper atmosphere and for rocket plumes and reentry. An SPS scenario of 400 launches per year for 10 yr was considered. The build-up of the contaminants in the atmosphere was projected to have no significant effects, even at the launch latitude. Neither would there by any dangerous ozone depletion. It was found that H, OH, and HO2 species would double in the thermosphere. No measurable changes in climate were foreseen.

Whitten, R. C.↗

Parametric studies with an atmospheric diffusion model that assesses toxic fuel hazards due to the ground clouds generated by rocket launches

Parametric studies were made with a multilayer atmospheric diffusion model to place quantitative limits on the uncertainty of predicting ground-level toxic rocket-fuel concentrations. Exhaust distributions in the ground cloud, cloud stabilized geometry, atmospheric coefficients, the effects of exhaust plume afterburning of carbon monoxide CO, assumed surface mixing-layer division in the model, and model sensitivity to different meteorological regimes were studied. Large-scale differences in ground-level predictions are quantitatively described. Cloud alongwind growth for several meteorological conditions is shown to be in error because of incorrect application of previous diffusion theory. In addition, rocket-plume calculations indicate that almost all of the rocket-motor carbon monoxide is afterburned to carbon dioxide CO2, thus reducing toxic hazards due to CO. The afterburning is also shown to have a significant effect on cloud stabilization height and on ground-level concentrations of exhaust products.

Stewart, R. B.↗

Constraining Fossil Fuel CO2 Emissions from Urban Area Using OCO-2 Observations of Total Column CO2

Satellite observations of the total column dry-air CO2(XCO2) are expected to support the quantification and monitoring of fossil fuel CO2 (ffCO2) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCO-2) XCO2 retrievals to optimize whole-city emissions, using a Bayesian inversion system and high-resolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: “plume city” located in relatively flat terrain, represented by Riyadh and Cairo; “basin city” located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least number of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 5, 8, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffXCO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local XCO2 enhancements associated with local biospheric XCO2 variations are shown, which potentially lead to biased estimates of ffCO2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.

Xinxin Ye↗

Comparison of Modeled Backscatter using Measured Aerosol Microphysics with Focused CW Lidar Data over Pacific

During NASA's GLObal Backscatter Experiment (GLOBE) II flight mission over the Pacific Ocean in May-June 1990, extensive aerosol backscatter data sets from two continuous wave, focused CO2 Doppler lidars and an aerosol microphysics data set from a laser optical particle counter (LOPC) were obtained. Changes in aerosol loading in various air masses with associated changes in chemical composition, from sulfuric acid and sulfates to dustlike crustal material, significantly affected aerosol backscatter, causing variation of about 3 to 4 orders of magnitude. Some of the significant backscatter features encountered in different air masses were the low backscatter in subtropical air with even lower values in the tropics near the Intertropical Convergence Zone (ITCZ), highly variable backscatter in the ITCZ, mid-tropospheric aerosol backscatter background mode, and high backscatter in an Asian dust plume off the Japanese coast. Differences in aerosol composition and backscatter for northern and southern hemisphere also were observed. Using the LOPC measurements of physical and chemical aerosol properties, we determined the complex refractive index from three different aerosol mixture models to calculate backscatter. These values provided a well-defined envelope of modeled backscatter for various atmospheric conditions, giving good agreement with the lidar data over a horizontal sampling of approximately 18000 km in the mid-troposphere.

Srivastava, Vandana↗

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗

Development of a global model for atmospheric backscatter at CO2 wavelengths

The variation of the aerosol backscattering at 10.6 micrometers within the free troposphere was investigated and a model to describe this variation was developed. The analysis combines theoretical modeling with the results contained within three independent data sets. The data sets used were obtained by the SAGE I/SAM II satellite experiments, the GAMETAG flight series, and by direct backscatter measurements. The theoretical work includes use of a bimodal, two component aerosol model, and the study of the microphysical and associated optical changes occurring within an aerosol plume. A consistent picture is obtained that describes the variation of the aerosol backscattering function in the free troposphere with altitude, latitude, and season.

Kent, G. S.↗

Development of global model for atmospheric backscatter at CO2 wavelengths

The improvement of an understanding of the variation of the aerosol backscattering at 10.6 micron within the free troposphere and the development model to describe this was undertaken. The analysis combines theoretical modeling with the results contained within three independent data sets. The data sets are obtained by the SAGE I/SAM II satellite experiments, the GAMETAG flight series and by direct backscatter measurements. The theoretical work includes use of a bimodal, two component aerosol model, and the study of the microphysical and associated optical changes occurring within an aerosol plume. A consistent picture is obtained, which describes the variation of the aerosol backscattering function in the free troposphere with altitude, latitude, and season. Most data are available and greatest consistency is found inside the Northern Hemisphere.

Kent, G. S.↗

Machine Learning Applications in Analyzing the Role of Shale Barriers and Baffles for CO2 Storage

This study uses machine learning to analyze microseismic data from the Illinois Basin Decatur Project (IBDP) and quantify CO₂ plume extents. By leveraging well logs, microseismic records, and CO₂ injection metrics, the research predicts subsurface CO₂ plume dynamics. Findings show vertical clustering of microseismic events near the injection well, with CO₂ periodically breaching barriers due to buoyancy. K-Means clustering performed best, achieving the highest Silhouette Score and lowest Davies-Bouldin Index. This capability is crucial for real-time monitoring and management of CO₂ sequestration sites, validated against physical models and IBDP data, reinforcing CO₂ geological sequestration's viability and enhancing management tools.

Carr, Timothy↗

UAS Payload Design for In-Situ Smoke Plume Sensing

To aid in the detection of harmful aerosols and trace gases emitted in wildfires and prescribed burns, we are designing a smoke-specific payload which can be flown on the Black Swift S2™ Uncrewed Aerial System (UAS) platform. The payload will be custom and mounted within the nosecone, equipped with a trace gas sensor suite and particle spectrometer for characterization of wildfire and prescribed burn emissions. This data will aid in the improvement of HYSPLIT3 modeling to make more informed decisions regarding prescribed burns, particularly for mountain valleys in the Pacific Northwest. The trace gas suite will be composed of 8 low-cost trace gas sensors (CH4, CO2, CO, HCN, NO2, NO, O3, and Volatile Organic Compounds (VOCs)). Portable Optical Particle Spectrometer (POPS) measures particle size range between 0.14 to 3 µm, which is crucial for assessing public health impact, air quality, and visibility.

Henry Miller↗

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

Geological carbon sequestration (GCS) involves injecting CO2 into subsurface geological formationsfor permanent storage. Numerical simulations could guide decisions in GCS projects by predictingCO 2 migration pathways and the pressure distribution in storage formation. However, these simula-tions are often computationally expensive due to highly coupled physics and large spatial-temporalsimulation domains. Surrogate modelling with data-driven machine learning has become a promis-ing alternative to accelerate physics-based simulations. Among these, the Fourier neural operator(FNO) has been applied to three-dimensional synthetic subsurface models. Despite its good accuracyin simulating CO 2 plume migration, it requires large computational resources in training and alsolacks generalizability. Here, to further improve performance, we have developed a nested Fourier-DeepONet by combining the expressiveness of the FNO with the modularity of a deep operatornetwork (DeepONet). This new framework is twice as efficient as a nested FNO for training and has atleast 80% lower GPU memory requirement due to its flexibility to treat temporal coordinates sepa-rately. These performance improvements are achieved without compromising prediction accuracy.In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond thetraining range has been thoroughly evaluated. Nested Fourier-DeepONet outperformed the nestedFNO for extrapolation in time with more than 50% reduced error. It also exhibited good extrapolationaccuracy beyond the training range in terms of reservoir properties, number of wells, and injectionrate.

Lee, Jonathan E. [Department of Chemical and Envir↗

Afterbody Heat Flux Measurements in the NASA Ames HFFAF Ballistic Range

In order to measure afterbody heat fluxes over a model in the ballistic range, the required modifications to a proven technique for measuring forebody heat fluxes are described. This involves the use of an extended helium gas plume to remove the glowing wake and the use of special high conductivity, high temperature capable graphite-filled plastic for the afterbody. The models and test conditions are described. Data in the form of plots of the surface temperature of the models are presented. Finally, experimental and computational fluid dynamic (CFD) heat flux data for forebody and afterbody heat fluxes are presented and compared. Data are presented for a 45 degree sphere-cone (with a projecting rear stud) at 2.70 km/s and for a sphere at 4.76 km/s. Both models were launched into 76 Torr of CO2 gas. The experimental forebody heat fluxes were within 1.5% of the CFD values. The experimental afterbody heat fluxes were within 1% of the CFD values for the sphere, but only 51% of the CFD values for the sphere-cone.

Bogdanoff, David W.↗

Deep Learning-based Parameterization of Complex 3D CO2 Saturation Data in Large-scale Geological Carbon Storage

In deep learning (DL), dimension reduction plays a pivotal role in improving training efficiency and minimizing overfitting, especially when working with complex datasets like three-dimensional (3D) saturation data. In the context of geological carbon storage (GCS), 3D saturation data introduces unique challenges due to its sparse nature and sharp transitions at plume boundaries, known as shock fronts. To tackle these challenges, we developed a novel DL framework that combines dimension reduction with advanced 3D reconstruction techniques. Our approach utilizes latent variables derived from 2D average saturation fields to efficiently capture the essential features of high-dimensional data while reducing the number of variables. This enhances both the robustness and accuracy of DL models, making the framework more practical for real-world applications. By offering a tailored solution for modeling complex 3D saturation dynamics, this framework holds significant potential for environmental monitoring, energy storage, and other geological applications.

Wang, Hongsheng [University of Texas at Austin]↗

Primordial Synthesis of Amines and Amino Acids in a 1958 Miller H2S-Rich Spark Discharge Experiment

Archived samples from a previously unreported 1958 Stanley Miller electric discharge experiment containing hydrogen sulfide (H2S) were recently discovered and analyzed using high-performance liquid chromatography and time-of-flight mass spectrometry. We report here the detection and quantification of primary amine-containing compounds in the original sample residues, which were produced via spark discharge using a gaseous mixture of H2S, CH4, NH3, and CO2. A total of 23 amino acids and 4 amines, including 7 organosulfur compounds, were detected in these samples. The major amino acids with chiral centers are racemic within the accuracy of the measurements, indicating that they are not contaminants introduced during sample storage. This experiment marks the first synthesis of sulfur amino acids from spark discharge experiments designed to imitate primordia! environments. The relative yield of some amino acids, in particular the isomers of aminobutyric acid, are the highest ever found in a spark discharge experiment. The simulated primordial conditions used by Miller may serve as a model for early volcanic plume chemistry and provide insight to the possible roles such plumes may have played in abiotic organic synthesis. Additionally, the overall abundances of the synthesized amino acids in the presence of H2S are very similar to the abundances found in some carbonaceous meteorites, suggesting that H2S may have played an important role in prebiotic reactions in early solar system environments.

Parker, Eric T.↗

Hero Carbonsafe Phase 2 Project in the Columbia River Basalt Group: Technical Program Overview

The Hermiston, Oregon Basalt CarbonSAFE Phase II project (HERO CarbonSAFE) seeks to accelerate the deployment of commercial carbon dioxide (CO2) storage projects in basaltic rocks. Hermiston is located near the center of the Columbia River Basalt Group (CRBG), which is one of the largest basalt flows in the US. Basalt CO2 storage has potential advantages to conventional saline storage reservoirs including 1. The potential for rapid mineralization of CO2, 2. associated decreases in pressure and CO2 migration risks, 3. reduced long-term monitoring requirements with respect to plume tracking, 4. widespread geographic distribution and, 5. large storage potential due to thickness, porosity, and CO2 interactions with basalt. For locations such as the Pacific Northwest (PNW), Hawaii, Iceland, India and Japan, whose localities are isolated from large sedimentary basins offering conventional saline storage options, basalt may offer the only feasible option for local CO2 storage. However, mineralization/basalt storage still has many uncertainties, as there are limited field-scale assessments of CO2 storage in basalt. There are significant uncertainties hindering the effective implementation of carbon capture utilization and storage (CCUS) in basalt. These include the lack of proven storage capacities, challenges in methodologies for modeling the area of review in igneous formations, limited understanding of mineralization kinetics and timing, and uncertainties in injectivity. Additionally, the domestic availability of specialized services and drilling expertise is constrained, and existing CCUS permitting and regulatory frameworks, originally developed for conventional saline reservoirs, may not adequately address the unique requirements of basalt systems. HERO CarbonSAFE is designed to address major research gaps and uncertainties associated with basalt storage. Specifically, the project will assess the feasibility of CO2 injection in the deep layered basalts of the CRBG, long-term storage (mineralization), practical approaches for large-scale implementation (50+ million metric tons of CO2 over 30 years), lithology-specific risks, and the technoeconomic potential for CO2 storage in basalts.

58 GEOSCIENCES↗

Emissions Relationships Among Western Forest Fire Plumes: II. Plume Typing for Sources of Ozone and Aerosol Absorption

Previous studies of emission factors from biomass burning are prone to largeerrors since they ignore the interplay of mixing and varying pre-fire backgroundCO2 levels. Such complications severely affected our studies of 446 forest fireplume samples measured in the Western US by the science teams of NASAs SEAC4RS and ARCTAS airborne missions. Consequently we propose a MixedEffects Regression Emission Technique (MERET) to check techniques like theNormalized Emission Ratio Method (NERM), where use of sequentialobservations cannot disentangle emissions and mixing. We also evaluate asimpler consensus technique. All techniques relate emissions to fuel burnedusing Cburn Ctot added to the fire plume, where Ctot (CO2 + CO). Mixed-effectsregression can estimate pre-fire background values of Ctot (indexed byobservation j) simultaneously with emissions factors indexed by individualspecies i, xi (Cburn )i,j., MERET and consensus require more than twoemissions indicators. Our studies excluded samples where exogenous CO orCH4 might have been fed into a fire plume, mimicking emission.We sought to let the data on 13 gases and particulate properties suggest clustersof variables and plume types, using non-negative matrix factorization (NMF).While samples were mixtures, the NMF unmixing suggested purer burn types.Particulate properties (bscat, babs, SSA, AE) and gas-phase emissions were interrelated.Finally, we sought a simple categorization useful for modeling ozone productionin plumes. Two kinds of fires produced high ozone: those with large fuel nitrogenas evidenced by remnant CH3CN in the plumes, and also those from veryintense large burns. Fire types with optimal ratios of delta-NOydelta-HCHO associate with the highest additional ozone per unit Cburn, Perhaps theseplumes exhibit limited NOx binding to reactive organics. Perhaps these plumesexhibit limited NOx binding to reactive organics.

ozone↗

The Effect of Europa and Enceladus Analog Seawater Composition on Isotopic Measurements of Volatile CO2

Science goals for icy ocean worlds missions include characterizing the chemical compositionof the surface and interior using remote sensing and in situ techniques. The next class of flightmass spectrometers for these missions will obtain compositional identifications and isotope ratiomeasurements of volatiles evolved from the ice surface (exosphere) and plumes. These massspectra will be combined with data from other flight instruments to infer the composition of theinterior from volatiles. To ensure accurate interpretation of these measurements, it is critical toverify whether the fundamental assumption that volatiles observed in icy ocean world exospheresor plumes will be a direct reflection of the sub-ice ocean. The present study evaluates whether isotopologues from an initial CO2 gas fractionate by interacting with seawater (brine) of varyingsalt composition and concentration. δ13CCO2 are affected by the pH of the brine and subsequentspeciation of {CO2}, where {CO2} represents the combination of CO2, H2CO3, HCO3-, and CO32-.{CO2} for low pH brines hypothesized for Europa will preferentially speciate as CO2. Analyzedδ13CCO2 for low pH brines are within error of the original δ13CCO2, demonstrating that volatile CO2in a low pH system will be a direct reflection of the original CO2. However, Europa’s radiativeenvironment and rapid depressurization due to plume ejection may impose fractionation effects.In contrast, high pH systems relevant to Enceladus or a more alkaline Europa are expected toform all carbonate species, while favoring speciation as HCO3-. High pH brines in theseexperiments include both an original CO2 gas and an isotopically distinct HCO3- (from NaHCO3salt). These alkaline experiments demonstrate that δ13CCO2 values are highly variable, and dependon the concentration of the dominant carbonate species, (Na)HCO3-. Mass balance estimatesindicate that measured δ13CCO2 is a thermodynamically predictable mixture of both carbonsources, suggesting that measurements of δ13C at Enceladus would directly reflect of the sourcesof CO2 and carbonate buffering in the ocean. δ18O measurements for CO2 interacting with KCland MgCl2 follow established models for δ18O-ionic strength. CO2 interacting with MgSO4,Na2SO4, and NaCl demonstrate an offset from established δ18O-ionic strength models dependingon the concentration of initial CO2. These results suggest that current predictive models for δ18Oin brines need to be resolved for changing concentrations of CO2

Ocean Worlds↗