Movement Of CO2 Research Articles

A physics-constraint neural network for CO2 storage in deep saline aquifers during injection and post-injection periods

CO2 capture and storage is a viable solution in the effort to mitigate global climate change. Deep saline aquifers, in particular, have emerged as promising storage options, owing to their vast capacity and widespread distribution. However, the task of proficiently monitoring and simulating CO2 behavior within these formations poses significant challenges. To address this, we introduce the physics-constraint neural network for CO2 storage (CO2PCNet), a model specifically designed for simulating and monitoring CO2 storage in deep saline aquifers during injection and post-injection periods. Recognizing the significant challenges in accurately modeling the distribution and movement of CO2 under varying permeability conditions, the CO2PCNet integrates the principles of physics with the robustness of deep learning, serving as a powerful surrogate model. The architecture of CO2PCNet starts with an encoder that adeptly processes spatial features from overall mole fraction (zCO2) and pressure fields (Pl), capturing the complex dynamics of a CO2 trajectory. By incorporating permeability information through a conditioning step, the network ensures a faithful representation of the influences on CO2 behavior in subsurface conditions. A ConvLSTM module subsequently discerns temporal evolutions, reflecting the real-world progression of CO2 plumes within the reservoir. Lastly, the decoder precisely reconstructs the predictive spatial profile of CO2 distribution. CO2PCNet, with its integration of convolutional layers, recurrent mechanisms, and physics-informed constraints, offers a refined approach to CO2 storage simulation. This model offers the potential of utilizing advanced computational methods in advancing CCS practices.

Analysis of dynamic characteristics and influencing factors of CO2 low-permeability coal reservoir sequestration

ABSTRACT Abandoned coal seams can be an important carrier for CO2 geological storage. Considering the gas seepage-diffusion and physical adsorption coupling characteristics in the process of CO2 adsorption and storage in coal and rock, a two-dimensional model of coupled flow-solidity for geological storage of CO2 in low-permeability reservoir with double voids was established by introducing the Zhang Hongbin model algorithm and adding the Klinkenberg effect and the compression effect of the rock skeleton in coal reservoirs in the controlling equation for rock deformation. The coupled flow-solid model was solved by using the PDE equation of COMSOL Multiphics program, and the simulation results difference between the new model and the traditional model in terms of sequestration dynamics were compared. The dynamic characteristic of reservoir gas pressure, formation stress, permeability and sequestration density in the process of CO2 geologic sequestration and injection were analyzed, and the influences of injection pressure and injection well diameter on the amount of CO2 sequestration were explored. The results show that the new model is more reasonable for calculating reservoir gas pressure and permeability compared with the Palmer-Mansoori model (PM model), and can simulate the free-state seepage movement of CO2 in the fracture system as well as its physical adsorption process compared with the single-heavy pore medium model. With continuous CO2 injection, the maximum sequestration density was raised to a limit value of about 1000 kg/m3 after 1 year. The date of reaching the limit of the sequestration volume was advanced by about 45 d when the positive pressure of the injected gas was increased from 10 kPa to 50 kPa. This model can reproduce the main parameters including, when affecting the effect, and realize the calculation of parameters such as CO2 density reaching the limit value, sealing limit day, sealing limit amount, which can provide a theoretical basis for further deep understanding of CO2 geological sealing law and scientific development of gas injection scheme.

Automatic detection of CO2 rebreathing during BiPAP ventilation

Carbon dioxide rebreathing (CO2 rebreathing) significantly influences respiratory drive and the work of breathing during BiPAP ventilation. We analyzed CO2 movement during BiPAP ventilation to find a method of real time detection of CO2 rebreathing without the need of CO2 concentration measurement sampled from the circuit (method expensive and not routinely used). Observational study during routine care in 15 bed university hospital ICU. At 18 patients who required BiPAP ventilation, intubated or during noninvasive ventilation, during weaning period airflow, pressure and CO2 concentration signals were registered on both sides of venting port and 17 respiratory parameters were measured or calculated for each of 4747 respiratory cycles analyzed. Based on CO2 movement (expiration–inspiration sequences) 3 types of cycle were identified, type I and II do not induce rebreathing but type III does. To test differences between the 3 types ANOVA, t-tests, and canonical discriminant analysis (CDA) were used. Then a multilayer perceptron (MLP) network, a type of artificial neural network, using the above parameters (excluding CO2 concentration) was applied to automatically identify the three types of respiratory cycles. Of the 4747 respiratory cycles, 1849 were type I, 1545 type II, and 1353 type III. ANOVA and t-tests showed significant differences between the types of respiratory cycles. CDA confirmed a correct apportionment of 93.9% of the cycles; notably, of 97.9% of type III. MLP automatically classified the respiratory cycles into the three types with 98.8% accuracy. Three types of respiratory cycles could be distinguished based on CO2 movement during BiPAP ventilation. Artificial neural networks can be used to automatically detect respiratory cycle type III, the only inducing CO2 rebreathing.

Reaction mechanism of catalytic gasification by calcium-based catalysts and oxidized coal residues in coalfield fire zones

Fires originating from coal spontaneous combustion within coalfields result not only in substantial coal resource depletion but also producing residual low-activity pyrolysis coal chars exhibiting varying degrees of oxidation. These chars develop progressively through successive heat penetration at the fire front and post-fire extinguishment phases. This paper focuses on the alkaline earth metal-activated catalytic gasification of residual oxidized coal in fire zones, constructs a carbon-based model of oxidized coal in fire zones. The results show that the reaction active sites of the oxidized coal carbon matrix model are mainly concentrated on the carbon atoms at the end of the aromatic ring. During catalytic gasification, the calcium-based catalyst engages with these active sites, forming a preliminary catalyst. The transformation of oxidized coal into CO primarily occurs through two distinct routes. Calcium attaches to the surface of the oxidized coal’s carbon-based structure, establishing active sites. Acting as a facilitator, it aids the movement of CO2 to the carbon-based surface, leading to its further breakdown into CO. The catalytic species containing calcium persistently amalgamates with active sites on coal coke surface, fostering the release of additional CO. Moreover, these catalytic species with calcium also bind CO2 and unite with active coal coke sites, generating carbon–oxygen complexes on the surface. These complexes are thermally unstable and decompose, yielding CO and initiating the formation of fresh active sites on the coal coke surface. Consequently, they interact further with calcium-based catalytic species, culminating in the creation of catalyst precursors, which drive a recurrent catalytic reaction process.

Estimation of the Hazardous Chemical Leakage Scale Inside Buildings Using CFD

Increased industrialization and aging infrastructure have resulted in leaks of hazardous chemicals, such as CO. Leak modeling is crucial to developing emergency response strategies. Therefore, we simulated the time to criticality (TTC), which is the time to reach the threshold limit for occupational exposure, of a CO leak. The basis of the study is a fire dynamics simulator, a computational fluid dynamics model that was used to investigate the movement of CO in various scenarios, including using different building layouts and areas, temperatures, and leak diameters. Multiple regression analysis was performed to obtain regression equations for the TTC as a function of the independent variables. Ultimately, we found that the type of dispersion varies with respect to the temperature-dependent density of CO, and, among the independent variables, the leak diameter had the strongest effect on the TTC. The regression equations with logarithmic conversion were validated and found to have higher accuracy than those without logarithmic conversion. The findings provide useful information for developing emergency response plans regarding leak size in the case of hazardous chemical leakage. However, empirical studies of different gas types and leakage scenarios are required.

The Analysis of Permeability Influence on CO2 Plume based on Reservoir Simulation

Abstract Permeability is critical in site characterization and geoscience studies for carbon capture and storage projects. There is significant uncertainty of CO2 movement in the subsurface caused by permeability. This study aims to analyze the influence of permeability on the movement of CO2 plumes using a synthetic single-porosity model based on reservoir simulation. By simplifying geomechanics, employing tornado experimental design, as well as utilizing Pearson and Spearman correlations from 30,000 neural network proxy models based on Latin Hypercube and Monte Carlo experimental design, this research successfully explains the impact of permeability on CO2 movement. The reservoir can withstand pressures up to 6500 psi without rock failure. The total CO2 injection with a 90% probability is ∼1.3 TSCF equivalent, with an injection rate of 30 MMSCFD, optimized for a duration of 120 years. Initially, the CO2 movement tends to be upward during injection due to gravitational effects, but over time, it tends to move laterally. Vertical permeability exhibits a negative correlation with total CO2 injection, lateral distribution of CO2 plumes, and CO2 solubility in water. On the other hand, horizontal permeability shows a positive correlation with total CO2 injection. Factors such as perforation location and layer thickness also influence the extent of permeability’s role. However, the lateral and vertical movement of CO2 in this study has not been fully identified, and more complex quantification formulas are needed in commercial simulators. Despite the limitations in data and computational resources, this research successfully explains the movement of CO2 plumes and highlights the importance of other factors such as porosity, perforation location, layer thickness, among others. The recommendations of this study include the use of more complex quantification formulas to model the movement of CO2 plumes, along with increasing the complexity of the model.

Robust CO2 plume imaging by joint tomographic inversion using distributed pressure and temperature measurements

The scientific community has become increasingly interested in geological CO2 sequestration and CO2 enhanced oil recovery (EOR). The tracking of the CO2 propagation in both space and time during geologic sequestration is necessary to ensure the secure and effective handling of a site for CO2 injection. Our objective is to develop efficient and novel models and monitoring techniques for visualizing CO2 plumes using field measurements. As a first step, the streamline-based data integration approach is extended to include data from distributed temperature sensors (DTS). The DTS and pressure data are then jointly history matched using a hierarchical workflow combining evolutionary and streamline methods. As a final step, we will create maps that visualize CO2 propagation during the sequestration process based on saturation and streamline maps. We validate the extended streamline-based inversion method using a synthetic model. An application of the hierarchical workflow is then made to the CO2 geologic storage test site in Michigan, USA. Monitoring data includes bottom-hole pressure of the injection well, DTS data at the monitoring well, and distributed pressure measurements from several downhole sensors along the monitoring well. Based on the history matching results, the CO2 movement is largely limited to the zones intended for injection, which is in agreement with an independent warmback analysis of the temperature data. The novelty of this work is the extension of the streamline-based inversion algorithm for the DTS data, its field application to the Department of Energy regional carbon sequestration project, and potential extensions to other CO2-EOR and/or associated geological storage projects.

Competitive adsorption of CH4/CO2 in shale nanopores during static and displacement process

During the development of shale gas, various issues such as low individual well production, rapid decline, limited reservoir control, and low recovery rates have arisen. Enhancing shale gas reservoir recovery rates has consistently been a focal point and challenge within the industry. Therefore, this paper employs molecular dynamic (MD) simulation methods to study the adsorption and diffusion characteristics of CH4/CO2 at different temperatures and mixing ratios. It compares the effects of temperature and CH4/CO2 molar ratio changes on the selectivity coefficient, adsorption capacity, and diffusion coefficient of CH4/CO2. The paper also plots the displacement interface and the function of CH4/CO2 injection/residual amounts over time. Furthermore, it analyzes the adsorption capacity of molecules on the graphene surface, the migration capacity of molecules in the slit, and the displacement process of CH4 by CO2 on the nanoscale, revealing the microscopic mechanism of CH4/CO2 competitive adsorption and displacement. The research results indicate that the influence of temperature on the selectivity coefficient is not significant, with an average decrease of 3% for every 20 K rise in temperature. Pressure has a more pronounced effect on the selectivity coefficient, with values around 1.4 at low pressures and around 1.2 at high pressures. Elevating the mole fraction of CO2 in the binary gas mixture results in an increase in the total adsorption amount and an accelerated variation of adsorption amount with pressure. As the CH4 mole fraction rises, the diffusion coefficient of CH4 increases, while the diffusion coefficient of CO2 diminishes with an increasing CO2 mole fraction. Under identical conditions, CO2 exhibits a stronger adsorption capacity over CH4 in shale organic nanopores, resulting in a concave moon-shaped displacement interface in the model. The larger the pre-adsorption pressure of CO2, the more intense the movement of CO2 along the graphene surface, and the faster the diffusion speed of CO2 along the wall. In a displacement pore (the pore space used to provide the displacement location or site) with a diameter of 3 nm, at smaller pressure differentials (≤10 MPa), the residual amount of CH4 remains relatively stable without substantial alteration. However, at a pressure differential of 20 MPa, the residual amount of CH4 decreases rapidly, and the displacement efficiency significantly improves.

The role of water vapour on CO2 mobility on calcite surface during carbonation process for calcium looping: A DFT study

The presence of water vapour has been proven to stimulate carbonation for the calcium looping process, while its effect mechanism during the slow reaction stage still lacks insight understanding at the atomic level, where H2O molecules may interact with the product layer to affect the transportation of CO2. This study tried to reveal the role of water vapour on CO2 mobility on the calcite surface through density functional theoretical (DFT) calculation. H2O molecule has higher adherence to calcite surface than CO2, and it can react with CO3 to generate HCO3− and OH− ions. Then, the formed OH− ion above the surface layer can adsorb CO2. Moreover, H2O can also react with O2− defect to form OH− ions, and the OH ion at the deeper position can still adsorb CO2 through a two-step process with remarkable energy barriers. However, the formation of HCO3− can degrade the energy barriers to CO2 release from the calcite surface, owning to the weaker CO bond. Two directions of CO2 movement between anions were involved in this investigation, including crossing through the surface layer to the second layer and the movement inside the surface layer, where the higher mobility of CO2 from HCO3− to O2− ion occurs in both movement directions. For the case inside the surface layer, the movement from O2− ion to HCO3− has a higher energy barrier, indicating that the stimulation by H2O is a one-way effect, and the enhancement by H2O for CO2 mobility is caused by the reaction with CO32− other than O2− ion.

Numerical study on the effects of fracture on density-driven flows in CO2 sequestration

In this study, CO2 transport in density-driven flows within an ideal model of a fractured porous medium, which contains a single or two intersecting fractures, is investigated numerically. The study employs a multi-scale modeling in which the flow in the matrix is modeled by Darcy's law, while the flow in the fracture is modeled by the Navier–Stokes equations. Our study shows that a horizontal fracture minimally impacts CO2 distribution, and depending on its length, slightly reduces dissolved CO2 during sequestration by 1.5%–2.5%. Vertical fractures play a crucial role in redirecting CO2 movement within the matrix, guiding it toward the fractures and altering its original pathway. Notably, the observed oscillations of CO2-rich water between the interfaces of the vertical fracture highlight the flow consistency with the pore scale. The domain-scale circulation induced by the vertical fracture leads to a rapid increase in flux and dissolved CO2 mass, but early convection shuts down. The results demonstrate that a longer vertical fracture leads to earlier shut down of convection and a potential decrease in storage of over 11%. The flow behaviors observed in inclined fractures are akin to those in vertical fractures, as they disrupt the fingerlike structure of CO2 around the fracture, form the circulation around the fracture, and are accompanied by vortices at the top. Additionally, intersecting fractures can lead to dynamic interactions between the fractures, with high-angle fractures dominating mixing flow. Different fracture angle combinations minimally affect dissolution mass.

Probing the exchange of CO2 and O2 in the shallow critical zone during weathering of marl and black shale

Abstract. Chemical weathering of sedimentary rocks can release carbon dioxide (CO2) and consume oxygen (O2) via the oxidation of petrogenic organic carbon and sulfide minerals. These pathways govern Earth's surface system and climate over geological timescales, but the present-day weathering fluxes and their environmental controls are only partly constrained due to a lack of in situ measurements. Here, we investigate the gaseous exchange of CO2 and O2 during the oxidative weathering of black shales and marls exposed in the French southern Alps. On six field trips over 1 year, we use drilled headspace chambers to measure the CO2 concentrations in the shallow critical zone and quantify CO2 fluxes in real time. Importantly, we develop a new approach to estimate the volume of rock that contributes CO2 to a chamber, and assess effective diffusive gas exchange, by first quantifying the mass of CO2 that is stored in a chamber and connected rock pores. Both rock types are characterized by similar contributing rock volumes and diffusive movement of CO2. However, CO2 emissions differed between the rock types, with yields over rock outcrop surfaces (inferred from the contributing rock volume and the local weathering depths) ranging on average between 73 and 1108 tCkm-2yr-1 for black shales and between 43 and 873 tCkm-2yr-1 for marls over the study period. Having quantified diffusive processes, chamber-based O2 concentration measurements are used to calculate O2 fluxes. The rate of O2 consumption increased with production of CO2, and with increased temperature, with an average O2:CO2 molar ratio of 10:1. If O2 consumption occurs by both rock organic carbon oxidation and carbonate dissolution coupled to sulfide oxidation, either an additional O2 sink needs to be identified or significant export of dissolved inorganic carbon occurs from the weathering zone. Together, our findings refine the tools we have to probe CO2 and O2 exchange in rocks at Earth's surface and shed new light on CO2 and O2 fluxes, their drivers, and the fate of rock-derived carbon.

Opportunities for rail in the transport of carbon dioxide in the United States

The deployment of carbon management strategies like carbon capture and storage (CCS) and carbon dioxide removal (CDR) at scale will require significant investments in transport infrastructure to deliver CO2 to reliable storage. While pipeline transport has dominated the conversation due to economic reasons, there is increasing evidence that other modes may become viable alternatives when considering scale, regional opportunities, and social acceptance. This paper assesses the viability of rail for CO2 transport in the United States using market analysis, techno-economic assessment and geographic information systems mapping. We believe rail presents many advantages, notably in existing infrastructure with established right-of-ways, but also as an instrument to address unwanted effects of our energy transition, particularly in coal communities. We find that the strategic replacement of coal as a freight commodity could translate into 100 Mt/yr of CO2 movement by rail by 2050, and support up to 60,000 jobs in that industry. Further, we find that while rail pricing is notoriously volatile, there is strong support for rail being the least cost option over pipeline for volumes under 2 Mt CO2 per year, which aligns well with smaller, more risk-averse, and distributed carbon management projects that are scheduled to deploy over the next decade. Rail can also be an alternative in regions where CO2 pipeline projects have had limited success, like in the Midwest, where CO2 is captured from ethanol plants that are already serviced by rail networks. Likewise, rail can service roughly 25% of point-source CCS opportunities that are not proximal to projected trunk pipeline networks, of which 94% are located 1-mile from railroad. Finally, rail may be an integral part of CDR development in regions that are not coterminous with geologic storage, particularly in the Western and Northern US.

Utilizing Direct Membrane Deposition to Improve the Performance of Forward-Bias Bipolar Membrane CO2 Electrolysers

The electrochemical conversion of CO2 to multi-carbon products (C2+), such as ethylene and ethanol, is an attractive technology towards achieving net zero carbon emission goals. Among the available configurations of CO2 electrolysers, those employing a bipolar membrane (BPM) in forward-bias mode (f-BPM) reduce CO2 loss to the anode – a problem commonly faced in traditional anion exchange membrane (AEM) electrolysers. Therefore, carbon efficiency (the percent of input CO2 that is converted to C2+ products) and system operational costs can be improved.In f-BPM electrolysers, (bi)carbonate ions move through the AEM then combine with protons moving through the cation exchange membrane (CEM) to regenerate CO2 and H2O at the AEM|CEM interface. Recent reports have implemented a porous AEM structure or an added AEM|CEM interface channel to aid the movement of CO2 from the AEM|CEM interface to the cathode and, thus, avoid blistering. Despite the advantage of f-BPM CO2 electrolysers, their performance is limited by the parasitic H2 evolution reaction (>20% Faradaic efficiency, or FE) and the low C2+ FE (<40%) at industrially relevant reaction rates (≥200 mA cm-2). We attribute this performance limitation to the unintended gaps between the used AEM and CEM. Inadequate contact between the AEM and CEM is anticipated to reduce the extent of local CO2 regeneration and promote unwanted proton crossover to the cathode; both phenomena could be contributing to the commonly observed FEs.In this report, we enhanced the contact between the AEM and CEM through the use of direct membrane deposition (DMD) over a Cu-based cathode. The DMD approach enabled modular control over the AEM and CEM thicknesses and structures, which improved ion and gas transport. Through electrochemical impedance spectroscopy, the DMD system was observed to improve the mass transport by >58% compared to a system that is similar to current f-BPM electrolysers (i.e., control system). The facilitated mass transport resulted in a reduction of the operating cell potential (by 0.84 V) and an enhancement of the C2+ FE to 65% (from 29% in the control system) at 300 mA cm-2. The flexibility of the DMD approach also enabled the fabrication of asymmetric BPMs, resulting in a record low H2 FE of 12% at 300 mA cm-2. We also demonstrated a 79% single-pass CO2 conversion (SPC) with 67% C2+ FE, resembling the highest simultaneous SPC and C2+ FE achievement at high current density (300 mA cm-2)among current f-BPM electrolysers. The DMD benefit was also applicable to other types of CO2 electrolysers, such as CO2-to-CO silver catalyst electrolysers, in which the CO FE was boosted to 90% (from 65% in the control system) at 90 mA cm-2. Figure 1

Elastic properties of unconsolidated sandstones of interest for carbon storage

AbstractUnconsolidated sandstones are attractive targets for underground storage of carbon due to their high porosity and permeability. Monitoring of injection and movement of CO2 in such formations using elastic waves requires an understanding of the acoustic properties of the sandstone. Current approaches often use the so‐called soft‐sand model in which a Hertz–Mindlin model of the acoustic properties at high porosity is mixed with the acoustic properties of the mineral phase to predict the acoustic properties over the entire porosity range. Using well‐log data from two unconsolidated sand formations of interest for CO2 storage, we discuss the limitations of this model and provide an alternative approach in which the mechanical properties of grain contacts are obtained by inversion, and the properties of infill material lying within the pore space are estimated. The formations considered are the Paluxy Formation in Kemper County, Mississippi, and the Frio Formation near Houston, Texas. The ratio of the normal to shear compliance of the grain contacts is found to be significantly less than unity for both formations. This implies that the grain contacts are more compliant in shear than in compression. However, the grain contact compliance is higher and the ratio of the normal to shear compliance is lower for the Frio example than for the Paluxy case, and this may lead to sliding at grain contacts with low shear compliance and transport of grains during fluid flow, particularly if CO2 acts to weaken any cement that may be present at the grain contacts. Such transport was suggested by Al Hosni et al. in explaining why the magnitude of the time‐lapse effect due to the injection of CO2 at the Frio CO2 injection site is greater than predicted using conventional rock physics models. A simple model of the mechanical properties of infill material lying within the pore space suggests that the bulk and shear moduli of infill material in the Paluxy case are significantly higher than the Frio case, consistent with the lower grain contact compliance in the Paluxy case.

Residual Saturation Effects on CO2 Migration and Caprock Sealing: A Study of Permeability and Capillary Pressure Models

In CO2 geological storage, multiphase flow plays a vital role in the movement and distribution of CO2. However, due to the limitations of fluid buoyancy and capillary forces, CO2 encounters challenges in penetrating the caprock, and the potential for leakage remains a concern due to variations in injection conditions. The migration and distribution of CO2 in the process of CO2 geological storage in saline formations are determined by relative permeability and capillary pressure, which are key factors. Consequently, this study focuses on two essential models: relative permeability and capillary pressure models. A two-dimensional isothermal reservoir–caprock model was constructed, utilizing data from the Shenhua CCS demonstration project. The analysis indicates that the core parameters in the model are residual gas saturation and residual water saturation. Specifically, residual gas saturation governs the diffusion distance of CO2 within the reservoir–caprock system, while its combined effect with residual water saturation affects the permeation rate of CO2. Through the application of the Analytic Hierarchy Process (AHP) to analyze the impact of different models on caprock integrity, it was determined that when selecting caprock models and optimizing parameters, precedence should be given to models with lower residual saturation and caprocks that offer sufficient capillary pressure for optimal sealing effects. These research findings can serve as references for practical CO2 storage projects, providing guidance on activities such as adjusting water injection strategies and controlling gas injection pressures to optimize geological storage efficiency.

Three‐axis borehole gravity monitoring for CO2 storage using machine learning coupled to fluid flow simulator

AbstractThe field of geophysics faces the daunting task of monitoring complex reservoir dynamics and imaging carbon dioxide storage up to several decades into the future. This presents numerous challenges, including sensitivity to parameter changes, resolution of obtained results and the cost of long‐term deployment. To effectively store CO2 subsurface, it is necessary to monitor and account for the injected CO2. The gravity method provides several advantages for CO2 monitoring, as changes in fluid saturation correspond directly and uniquely to observed density changes. Three‐axis borehole gravity has demonstrated significant promise as a next‐generation tool for reliably monitoring reservoir dynamics across a range of depths and sizes. However, the gravity inverse problem is highly ill‐posed, necessitating regularization that incorporates prior knowledge. To address this issue, we propose using a feed‐forward neural network, a machine learning method, to invert time‐lapse three‐axis borehole gravity data and monitor CO2 movement within a reservoir. By training the neural network on models that analyse changes in density and corresponding gravity responses resulting from perturbations made to the reservoir model, we can create scenarios that train the algorithm to identify unexpected CO2 migration in addition to the normal movement of CO2. Our method is demonstrated using reservoir models for the Johansen formation in offshore Norway. We convert reservoir saturation models into density changes and generate their corresponding three‐axis gravity data in a set of boreholes. Our results show that the developed machine learning inversion algorithm has high reliability and resolution for imaging density change associated with CO2 plumes, as demonstrated in the Johansen reservoir models utilized by the simulator. We also investigate machine learning inversion using regularization parameters and show that it is robust, with a strong tolerance for higher levels of noise. Our study demonstrates that the developed machine learning algorithm is a powerful tool for inverting three‐axis borehole gravity data and monitoring the migration and long‐term storage of injected CO2.

Low internal air space in plants with crassulacean acid metabolism may be an anatomical spandrel.

Crassulacean acid metabolism (CAM) is a photosynthetic adaptation found in at least 38 plant families. Typically, the anatomy of CAM plants is characterized by large photosynthetic cells and a low percentage of leaf volume consisting of internal air space (% IAS). It has been suggested that reduced mesophyll conductance (gm) arising from low % IAS benefits CAM plants by preventing the movement of CO2 out of cells and ultimately minimizing leakage of CO2 from leaves into the atmosphere during day-time decarboxylation. Here, we propose that low % IAS does not provide any adaptive benefit to CAM plants, because stomatal closure during phase III of CAM will result in internal concentrations of CO2 becoming saturated, meaning low gm will not have any meaningful impact on the flux of gases within leaves. We suggest that low % IAS is more likely an indirect consequence of maximizing the cellular volume within a leaf, to provide space for the overnight storage of malic acid during the CAM cycle.

Atomically dispersed Fe sites on TiO2 for boosting photocatalytic CO2 reduction: Enhanced catalytic activity, DFT calculations and mechanistic insight

The design of photocatalysts for the stable and efficient photocatalytic reduction of CO2 without sacrificial agents remains challenging. In this study, Fe atoms were anchored on the surface of TiO2 with atomic-level dispersion using a novel negative-pressure encapsulation and pyrolysis strategy. The photoelectrochemical test results confirmed that the introduction of single Fe atoms accelerated the separation of photogenerated carriers and enhanced the TiO2 utilization rate of visible light. The optimal catalyst with atomically dispersed Fe showed excellent photocatalytic conversion of CO2 to CO (48.2 μmol·g−1·h−1) and CH4 (113.4 μmol·g−1·h−1), whereas the TiO2 system produced only trace amounts of CO (2.7 μmol·g−1·h−1). The increased CO2 adsorption energy and movement of the d-band center toward the Fermi level confirmed that single Fe sites were more favorable for the adsorption of CO2. The differential charge density distribution of CO2 adsorbed on the catalyst surface confirmed the rapid transfer of electrons along the Ti-O-Fe-C path, and the Gibbs free energy calculation further confirmed that the Fe sites were conducive to reducing the energy barrier required for the reaction. In addition, the key intermediate (*COOH) of CO2 conversion to CH4 was detected by in situ diffuse reflectance infrared Fourier transform spectroscopy, and a possible reaction pathway was proposed. This work provides an effective strategy for designing single-atom catalysts that can efficiently reduce CO2 to high-value-added products.

Creating a virtual leaf.

When microscopy meets modelling the exciting concept of a 'virtual leaf' is born. The goal of a 'virtual leaf' is to capture complex physiology in a virtual environment, resulting in the capacity to run experiments computationally. One example of a 'virtual leaf' application is capturing 3D anatomy from volume microscopy data and estimating where water evaporates in the leaf and the proportions of apoplastic, symplastic and gas phase water transport. The same 3D anatomy could then be used to improve established 3D reaction-diffusion models, providing a better understanding of the transport of CO2 across the stomata, through the airspace and across the mesophyll cell wall. This viewpoint discusses recent progress that has been made in transitioning from a bulk leaf approach to a 3D understanding of leaf physiology, in particular, the movement of CO2 and H2O within the leaf.

Experimental study on the leakage temperature field of buried CO2 pipelines.

The leakage of small holes in the buried CO2 pipeline is not easy to detect, which leads to the problem of the inability to accurately trace the source of the pipeline repair in the later stage. This paper designs and builds an experimental system to simulate the leakage of buried CO2 pipelines and conducts experiments on the leakage of small holes in buried CO2 pipelines to investigate the changes in the surrounding soil temperature when they leak. The results showed that the type of movement of CO2 in porous media after it is released from the leak is "funneling." At a distance of about 50 mm from the horizontal, the temperature difference in the horizontal surface is smallest at the 50 cm closest to the vertical distance of the leak, while at a distance of 225 mm from the horizontal, the temperature difference in the horizontal surface is largest at the 70 cm farthest from the vertical distance of the leak. The research results can provide a theoretical basis for the later development of technologies that can quickly locate the leakage points of buried CO2 pipelines and accurately determine their leakage status.