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At least 415 records · Page 23

High-resolution national mapping of natural gas composition substantially updates methane leakage impacts

Methane is emitted from oil and gas operations alongside heavier hydrocarbons and non-hydrocarbon gases, shaping emissions management decision-making, including air quality impacts. Yet, most assessments assume fixed gas composition, overlooking significant spatial and temporal variations. Here, we generate a high-resolution, data-driven map of natural gas composition across the United States, reconstructing methane, heavier hydrocarbons, and non-hydrocarbon species using spatio-temporal interpolation and oil-and-gas production patterns. Our approach is able to reduce composition prediction errors by 39% in terms of Mean Absolute Error (MAE) compared to standard techniques and reveals that methane loss rates have been underestimated by more than 50% in some regions. Beyond methane, we uncover substantial variability in co-emitted gases, exposing blind spots in current emissions inventories and emissions management frameworks. Our work enables more accurate emissions assessments, guides targeted measurement strategies, and informs emissions management decision-making. It also provides a general framework for prediction in environmental applications that integrate sparse measurements with auxiliary variables.

03 NATURAL GAS↗

Hydrogen storage and geo-methanation in a depleted underground hydrocarbon reservoir

Coupling of power-to-gas processes with underground gas storage could effectively allow surplus electricity to be stored for later use. Depleted hydrocarbon reservoirs could be used as stores, but practical experience of hydrogen storage in such sites is limited. Here we present data from a field trial that stored 119,353 m 3 of hydrogen admixed to natural gas in a depleted hydrocarbon reservoir. After 285 days, hydrogen recovery was 84.3%, indicating the process’s technical feasibility. Additionally, we report that microbes mediated hydrogen conversion to methane. In laboratory experiments studying mesocosms that mimic real reservoirs, hydrogen and carbon dioxide were converted to methane (0.26 mmol l —1 h —1 evolution rate) reproducibly over 14 cycles in 357 days. This rate theoretically allows 114,648 m 3 of methane per year to be produced in the test reservoir (equivalent to ~1.08 GWh). Our research demonstrates the efficiency of hydrogen storage and the importance of geo-methanation in depleted hydrocarbon reservoirs.

08 HYDROGEN↗

Emergent constraints on future methane emissions from global wetlands

Future methane (CH 4 ) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH 4 emissions (eCH 4 ) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH 4 yr −1 increase in eCH 4 . We also identify an emergent relationship between contemporary temperature dependence and projected eCH 4 . When constrained by 163 site-year eddy-covariance measurements of eCH 4 , we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH 4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic eCH 4 at the 2020 level, comparable to the reductions committed under the Global Methane Pledge. However, the constraint is dominated by mid- and high-latitude observations, with limited tropical coverage, and uncertainties in projected wetland inundation contribute substantially to uncertainty in eCH 4 . Our findings reduce the uncertainty in projected wetland methane–climate feedback and highlight its potential impacts on methane mitigation efforts to slow global warming.

Zhang, Zhen [Chinese Academy of Sciences (CAS), Be↗

Role of catalytic nitrile decomposition in tricopper complex mediated direct partial oxidation of methane to methanol

Synthetic homogeneous system known to date performing methane to methanol conversion using O 2 as terminal oxidant is unique and based on copper complex with piperazine-based ligand (Cu 3 L in Fig. 1) in a medium of acetonitrile. Prior work have shown that in order to achieve catalytic turnover, hydrogen peroxide is needed to regenerate the active site. We show in this paper that reaction solvent based on organic nitrile decompose concurrently with methane activation and that in the absence of either acetonitrile, Cu complex or hydrogen peroxide, the catalytic turnover does not happen. We show in this manuscript that the direct methane oxidation to methanol might have been mediated by catalytic Radziszewski oxidation between acetonitrile and H 2 O 2 . Additionally we have discovered that in the absence of methane, peroxide mediated acetonitrile decomposition also makes methanol via a background reaction which was hitherto unknown.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Partial oxidation of methane to methanol on boron nitride at near critical acetonitrile

Abstract Direct catalytic conversion of methane to methanol with O 2 has been a fundamental challenge in unlocking abundant natural gas supplies. Metal-free methane conversion with 17% methanol yield based on the limiting reagent O 2 at 275 °C was achieved with near supercritical acetonitrile in the presence of boron nitride. Reaction temperature, catalyst loading, dwell time, methane–oxygen molar ratio, and solvent-oxygen molar ratios were identified as critical factors controlling methane activation and the methanol yield. Extension of the study to ethane (C2) showed moderate yields of methanol (3.6%) and ethanol (4.5%).

03 NATURAL GAS↗

Biochemistry of aerobic biological methane oxidation

Methanotrophic bacteria represent a potential route to methane utilization and mitigation of methane emissions. In the first step of their metabolic pathway, aerobic methanotrophs use methane monooxygenases (MMOs) to activate methane, oxidizing it to methanol. There are two types of MMOs: a particulate, membrane-bound enzyme (pMMO) and a soluble, cytoplasmic enzyme (sMMO). The two MMOs are completely unrelated, with different architectures, metal cofactors, and mechanisms. The more prevalent of the two, pMMO, is copper-dependent, but the identity of its copper active site remains unclear. By contrast, sMMO uses a diiron active site, the catalytic cycle of which is well understood. Here we review the current state of knowledge for both MMOs, with an emphasis on recent developments and emerging hypotheses. In addition, we discuss obstacles to developing expression systems, which are needed to address outstanding questions and to facilitate future protein engineering efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integration of triaxial testing and pore-scale visualization of methane hydrate bearing sediments

Understanding mechanical interactions between hydrate and hosting sediments is critical for evaluating formation stability and associated environmental impacts of hydrate-bearing sediments during gas production. While core-scale studies of hydrate-bearing sediments are readily available and some explanations of observed results rely on pore-scale behavior of hydrate, actual pore-scale observations supporting the larger-scale phenomena are rarely available for hydrate-bearing sediments, especially with methane as guest molecules. The primary reasons for the scarcity include the challenge of developing tools for small-scale testing apparatus and pore-scale visualization capability. We present a testing assembly that combines pore-scale visualization and triaxial test capability of methane hydrate-bearing sediments. This testing assembly allows temperature regulation and independent control of four pressures: influent and effluent pore pressure, confining pressure, and axial pressure. Axial and lateral effective stresses can be applied independently to a 9.5 mm diameter and 19 mm long specimen while the pore pressure and temperature are controlled to maintain the stability of methane hydrate. The testing assembly also includes an X-ray transparent beryllium core holder so that 3D computed tomography scanning can be conducted during the triaxial loading. This testing assembly permits pore-scale exploration of hydrate-sediment interaction in addition to the traditional stress-strain relationship. Exemplary outcomes are presented to demonstrate applications of the testing assembly on geomechanical property estimations of methane-hydrate bearing sediments.

Seol, Yongkoo (ORCID:0000000295163405)↗

An Experimental Investigation of Supercritical Methane Injection Characteristics in a CO2 Environment

Abstract Clean energy generation is gaining significant attention from industries, academia, and governments across the globe. The Allam cycle is one such technology that has been under focus due to its efficiency, environmental friendliness, and economics. This is a direct-fired cycle operating at supercritical conditions using carbon dioxide as a working fluid. Fuel or oxidizer jet mixing with CO2 is a vital phenomenon that governs combustion efficiency, and it is not well understood for the Allam cycle conditions. This paper experimentally investigated the jet characteristics of a methane jet injected into a subcritical to supercritical carbon dioxide environment. A wide range of injection pressures and temperatures were targeted between subcritical to supercritical conditions. Unlike previous studies, the current work focused on injecting lower-density (methane) jets into higher-density (carbon dioxide) environments. Schlieren imaging and methane absorption measurements were simultaneously performed with a CMOS high-speed camera and a 3.39 μm infrared laser. Specifically, we looked at the classical injection parameter of jet spreading angle, which was classically established to be mainly a density ratio function. Here, the jet cone angle was obtained from the postprocessed schlieren imaging. The jet cone angle is a critical characteristic parameter that describes the entrainment rate in a jet; thus, it is a crucial parameter in understanding the nature of the jet. The laser measurements were only used as an additional check to confirm the entry time of methane into the chamber filled with carbon dioxide. Notably, this paper makes a detailed comparison between the jet cone angles of jets with a density ratio. The result showed that the classical correlations, such as Abramovich's theory applied to submerged turbulent gas jets developed for low-density ratio jets, were unsuitable for higher-density ratio jets. It was also observed that the divergence angles were dependent not only on density ratio but also on other parameters such as pressure ratios and reduced pressures.

Engineering↗

Recovery of particulate methane monooxygenase structure and activity in a lipid bilayer

Bacterial methane oxidation using the enzyme particulate methane monooxygenase (pMMO) contributes to the removal of environmental methane, a potent greenhouse gas. Crystal structures determined using inactive, detergent-solubilized pMMO lack several conserved regions neighboring the proposed active site. We show that reconstituting pMMO in nanodiscs with lipids extracted from the native organism restores methane oxidation activity. Multiple nanodisc-embedded pMMO structures determined by cryo–electron microscopy to 2.14- to 2.46-angstrom resolution reveal the structure of pMMO in a lipid environment. The resulting model includes stabilizing lipids, regions of the PmoA and PmoC subunits not observed in prior structures, and a previously undetected copper-binding site in the PmoC subunit with an adjacent hydrophobic cavity. These structures provide a revised framework for understanding and engineering pMMO function.

Science & Technology - Other Topics↗

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗

Combined Mixed Potential Electrochemical Sensors and Artificial Neural Networks for the Quantificationand Identification of Methane in Natural Gas Emissions Monitoring

Sensors capable of quantifying methane concentration and discriminating between possible sources are needed for natural gas leak detection where multiple spatially overlapping sources including wetlands and agriculture may be present. We report on the fabrication by an additive manufacturing process of a four electrode La 0.87 Sr 0.13 CrO 3 , Indium Tin Oxide (In 2 O 3 90 wt%, SnO 2 10 wt%), Au, Pt mixed potential electrochemical sensor using yttria-stabilized zirconia (YSZ) as a solid electrolyte to natural gas detection. Artificial neural networks (ANNs) are used to automatically decode the possible source and concentration of methane. The ANNs trained on sensor data are capable of correctly discriminating between three sources of methane emissions from simulated mixtures of emissions from cattle, wetlands, or natural gas with >98% accuracy. Quantification error for methane in mixtures of CH 4 in air, CH 4 + NH3 in air, and simulated natural gas is less than 1.5% ppm when a two-temperature dataset is employed.

03 NATURAL GAS↗

Smart Methane Emission Detection System Development Final Report

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators.

03 NATURAL GAS↗

Methane Consuming Biocatalysts in Gas-Solid Reactor System

Carbon dioxide and methane are the two most abundant greenhouse gases with methane having a higher global warming potential (GWP) than carbon dioxide. Use of methanotrophs as a biocatalyst is a green alternative to chemical conversion of methane. Methanotrophs were immobilized in a 4-arm poly (-ethylene glycol)-tetra-acrylate, PEGTA, hydrogel that is supported by a 3D printed lattice containing micropores. The consumption rate of methane was 2.5 and 42 g CH 4 /L-hr in samples that were at 1 and 3 atm, respectively. A small increase in pressure of the system improves the consumption rate by almost 20x with minimal changes to the reactor system. This system relies on the mass transport of gas through a solid-like material rather than dissolving the gas in a liquid. Immobilization of cells in hydrogel allows for higher cell density and overall increased conversion rates compared to traditional stirred tank reactors. There are many other applications of the use of immobilized biological materials in polymers that require gas-phase reactions.

36 MATERIALS SCIENCE↗

Isolated Single Metal Atoms Supported on Silica for One Step Non-Oxidative Methane Upgrading to Hydrogen and Value-Added Hydrocarbons

Natural gas in the United States offers substantial economic opportunities due to its abundance but its transportation is challenging because its primary component, methane (CH 4 ), does not liquefy at ambient temperature and typical pressures. As a result, a significant portion of natural gas is either used for heat, flared in remote locations, or remains unutilized, presenting a lost economic opportunity and an environmental harm. Converting natural gas to larger hydrocarbons in an economically competitive manner would enable transportation of products and further boost the economy and reduce environmental footprint. Our research goal is to enable efficient non-oxidative methane conversion (NMC) via catalyst innovation to convert CH 4 in one-step to olefins and aromatics and hydrogen (H 2 ) co-product. The catalysts are made of supported single metal atoms and operated at medium-high temperatures. The single metal atoms achieve methane activation by heterogeneous surface dehydrogenation to generate a hydrocarbon pool and importantly limit coke formation. The integration of novel single atom catalysts in a short contact time microreactor enable unprecedented NMC performance that could lead to economically-feasible, distributed natural gas upgrading by advanced manufacturing and process intensification. Our innovated catalyst and reactor technology promise to tap into previously uneconomic natural gas resources, such as stranded, vented, and flared methane.

03 NATURAL GAS↗

Effect of Support on Iron-Based Catalyst Toward CO2-Free H2 Production From Methane Pyrolysis

The global demand for low-emission hydrogen production is increasing rapidly due to the potential for hydrogen to substitute conventional fossil fuels in energy related applications. Among all the current practical technologies – Steam Reforming of Methane (SMR), Water Electrolysis, and Methane Pyrolysis – methane pyrolysis has the potential to produce economical- and near-zero-emission hydrogen because the reaction produces a solid carbon by-product that can be monetized to offset production costs. However, this route is not without research challenges, and the selective formation of high-value carbon remains a critical issue. Supported nickel, iron, and cobalt, have been widely investigated for methane pyrolysis. Although iron-based catalysts are less active than Ni, iron catalysts offer less resistance to coke formation, are inexpensive, and have a longer lifetime. One area not sufficiently explored is the effect of support materials other than Al2O3 for the iron-based catalysts. Therefore, in this study we investigated a detailed variation of support material to study their influence on the catalytic performance. Moreover, this study offers a fair comparison because all catalytic materials were synthesized and studied under identical conditions, allowing a direct comparison of the obtained results; this is important because results reported in different publications in literature are often not comparable, due to very different reaction conditions.

Aireddy, Divakar Reddy↗

Enhanced Outcrop Methane Capture (Final Project Report)

This report provides the final status of the “Enhanced Outcrop Methane Capture (EOMC) Project” which was focused on drilling two new methane capture wells along the Fruitland Formation Outcrop for capture of methane and carbon dioxide which are naturally seeping from the Outcrop. The EOMC Project was focused on evaluating whether novel horizontal drilling technology will result in improved capture of methane and carbon dioxide which are naturally seeping from the Fruitland Formation Outcrop on Southern Ute tribal trust lands within the Southern Ute Indian Reservation (the “Reservation”).

01 COAL, LIGNITE, AND PEAT↗

Physics-Informed Neural Network (PINN) Prediction of Mixed Mass-Heat-Crystallization Limited Methane Hydrate Formation and Dissociation in Micro-Confinement

The creation and use of Physics-Informed Neural Networks (PINNs) for simulating the dynamics of methane hydrate formation and dissociation will be presented. The PINN framework's main benefit is its capacity to impose physical consistency with only a partial comprehension of the governing equations. This makes the algorithm especially useful for systems with little experimental evidence or a lack of theoretical knowledge. A strong basis for forecasting methane hydrate behavior over the verified operating ranges of 30.0-80.9 bar pressure and 1.0-4.0 K sub-cooling conditions is provided by the combination of conductive heat transfer equations and mixed mass-transfer–crystallization kinetics. PINNs were more accurate at predicting the mixed mass-heat-crystallization limited kinetics than conventional Artificial Neural Networks (ANNs), demonstrating remarkable predictive accuracy for methane hydrate production over the ANN model. The efficiency of incorporating physical limitations from first principles into machine learning frameworks for methane hydrate crystallizations is reinforced by these findings. For hydrate-related applications in energy generation, carbon sequestration, and climate modelling, our study establishes PINNs as a computational tool that is both scalable and efficient. The proven capacity to close the gap between conventional physics-based simulations and solely data-driven models creates new opportunities for expedited hydrate research and practical applications.

Hartman, Ryan L [NYU Tandon School of Engineering]↗

A Review of Offshore Methane Quantification Methodologies

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emissions from production platforms measured using downwind dispersion methods were 32 kg h−1 from 188 platforms; 118 kg h−1 from 104 platforms using mass balance methods; 284 kg h−1 from 151 platforms using aircraft remote sensing; and 19,088 kg h−1 from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depths moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantification methodologies.

Riddick, Stuart N. (ORCID:0000000316841843)↗