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In interface coupled dissolution-precipitation systems, the dynamics of the mineral-fluid interface depends on two intertwining processes: the dissolution of the primary mineral that is needed for subsequent precipitation and the passivation of the dissolution reaction as a result of secondary mineral precipitation. The resulting thickness and texture of the precipitating coating layer will affect the progression of geochemical reactions, flow and transport processes at the macroscopic scale. Understanding the interplay between macroscopic flow regimes and microscopic reaction mechanisms (e.g., nucleation and crystal growth pathways) in controlling the dynamics of the mineral-fluid interface has important implications for predicting natural weathering processes, scaling in the subsurface energy production systems, etc. In this study, we use a micro-continuum pore-scale reactive transport model to investigate the feedback loop between reaction rate and solute transport with explicit consideration of the surface passivation and the diffusion process through the coating layer, as well as the impacts of saturation-dependent nucleation rate on the textures of precipitates that will largely dictate the diffusion properties of the coating layer. Our model results highlight that the drastically different coating behaviors at the macroscopic scale and their dependence on solution supersaturation observed in previous column experiments are primarily controlled by the interplay between mineral reaction rates, advective flow, and diffusion through the dynamically forming coating layer. The diffusion properties of the coating layer also play a secondary but non-negligible role in shaping the evolution of the co-dissolution and precipitation system. The probabilistic nucleation model building on the framework of classical nucleation theory highlights the complex dependence of precipitates’ texture on solution chemistry and substrate properties, which can affect the diffusion proc

Purpose: Heavy and light rare earth elements (REEs) are critical to clean energy technologies, and thus the environmental impacts from their production are increasingly scrutinized. Most previous LCAs of REE production focus on sites producing light REEs. This research addresses this gap by collecting primary data from sites producing heavy rare earth oxides (HREOs) from ion-adsorption clays, conducting an LCA, and providing open-source life cycle inventory (LCI) datasets of HREO production for the LCA community. Methods: This study conducts a LCA based on acquired primary data from four mining sites in Jiangxi Province, China. The functional unit is 1 kg of mixed HREOs of 90% purity from ion-adsorption clays using the technology of in situ leaching. Previous studies have used the Ecoinvent database, relying mostly on European or global life cycle inventories (LCIs). Here, the Chinese Life Cycle Database provided China-specific reference life cycle inventories (LCIs) for all inputs and processes with the exception of electricity generation LCIs used in a scenario analysis, which were provided by Ecoinvent 3. Twelve impact categories were examined using Impact 2002+, USEtox 2.01, and IPCC methods. Results are provided as a bounded range, reflecting low and high estimates based on collected primary data. Results and discussion: Results show 1 kg of mixed HREOs emit 258–408 kg CO2e, and consume 270–443 MJ primary energy. These values fall within the range of previous LCAs that examined both bastnaesite/monazite deposits and ion-adsorption clays using literature values. Other impact categories considered are not similar across studies, however. Differences are due to variability in resource type and quality, technology, and modeling choices, such as reference LCI sources. Mining and extraction contribute most to impacts due to large quantities of chemicals for leaching and precipitation of REOs, and electricity consumption. Among chemicals, ammonium

Geochemical reactions add complexity to the characterization and prediction of fracture hydraulic properties because they depend on factors that are highly heterogeneous, such as mineral composition. However, systematic analyses of fracture evolution in mineralogically heterogeneous systems are still limited. In this study, we investigated fracture evolution in multimineral systems using a reduced dimension reactive transport model. The model was developed and tested based on experimental studies and addresses the complex morphological and geochemical changes that arise from the presence of multiple minerals of different reactivities. Numerical experiments were performed using randomly generated initial fracture geometries based on representative geostatistics, different categories of mineral composition, and a range of flow rates that are relevant to geologic carbon storage systems. The simulation results showed distinct dissolution regimes at different flow rates, each of which produced characteristic dissolution patterns and temporal evolutions of chemical reactions and fracture hydraulic properties. Overall, as flow rate increases, fracture evolution shifts from compact dissolution to fracture channelization to uniform dissolution. The corresponding flow rate for a given dissolution regime, however, varies considerably with mineral composition. Fracture evolution, especially in the flow regime that induces fracture channelization, is also affected by initial fracture geometry. The numerical experiments were used to develop a multireaction Damköhler number (mDa) for the prediction of fracture evolution, and fracture channelization in particular, in multimineral systems. The multireaction Damköhler number also provides a useful framework for the evaluation of caprock integrity in geologic carbon storage systems.

The roughness of solid surfaces influences mineral dissolution rates by affecting flow and transport in the near-surface regions and by increasing the surface area available for reaction. The impact of surface area is commonly accounted for by using the surface roughness factor (SRF), which is the ratio between the total surface area and the nominal or geometric surface area. The coupled impacts of hydrodynamics and transport, however, are rarely considered. In this study, we performed pore-scale reactive transport simulations in a series of synthetic 2D rough fractures to investigate the compound effects of surface roughness on the reaction rates in fractures. Simulation results show that while reaction rates increase with SRF, the increase is not linearly proportional to that of the surface area. Rather, local concentration gradients resulting from flow and transport processes limit the increase in the rate. In addition, surface roughness gives rise to concentration gradients that do not otherwise develop in the flat-surface geometries typically considered in modeling studies. To describe the impacts of the surface area increase on reaction rate at different roughness and flow velocities, three distinct regimes were identified. A unified mathematical relationship was also developed that allows the reaction rate in a rough fracture to be approximated by the well-mixed reactor reaction rate and a correction factor. The correction factor follows a power-law function of SRF, with the multiplying factor and exponent expressed as exponential functions of the Péclet and Damköhler number. This mathematical formulation provides a valuable upscaling approach for effective integration of sub-grid scale surface roughness in larger scale continuum models.

This study investigated how subsurface and atmospheric leakage from geologic CO2 storage reservoirs could impact the deployment of Carbon Capture and Storage (CCS) in the global energy system. The Leakage Risk Monetization Model was used to estimate the costs of leakage for representative CO2 injection scenarios, and these costs were incorporated into the Global Change Assessment Model. Worst-case scenarios of CO2 leakage risk, which assume that all leakage pathway permeabilities are extremely high, were simulated. Even with this extreme assumption, the associated costs of monitoring, treatment, containment, and remediation resulted in minor shifts in the global energy system. For example, the reduction in CCS deployment in the electricity sector was 3% for the “high” leakage scenario, with replacement coming from fossil fuel and biomass without CCS, nuclear power, and renewable energy. In other words, the impact on CCS deployment under a realistic leakage scenario is likely to be negligible. We also quantified how the resulting shifts will impact atmospheric CO2 concentrations. Under a carbon tax that achieves an atmospheric CO2 concentration of 480 ppm in 2100, technology shifts due to leakage costs would increase this concentration by less than 5 ppm. It is important to emphasize that this increase does not result from leaked CO2 that reaches the land surface, which is minimal due to secondary trapping in geologic strata above the storage reservoir. The overall conclusion is that leakage risks and associated costs will likely not interfere with the effectiveness of policies for climate change mitigation.

This paper presents a new method—the Technique of Iterative Local Thresholding (TILT)—for processing 3D X-ray computed tomography (xCT) images for visualization and quantification of rock fractures. The TILT method includes the following advancements. First, custom masks are generated by a fracture-dilation procedure, which significantly amplifies the fracture signal on the intensity histogram used for local thresholding. Second, TILT is particularly well suited for fracture characterization in granular rocks because the multi-scale Hessian fracture (MHF) filter has been incorporated to distinguish fractures from pores in the rock matrix. Third, TILT wraps the thresholding and fracture isolation steps in an optimized iterative routine for binary segmentation, minimizing human intervention and enabling automated processing of large 3D datasets. As an illustrative example, we applied TILT to 3D xCT images of reacted and unreacted fractured limestone cores. Other segmentation methods were also applied to provide insights regarding variability in image processing. The results show that TILT significantly enhanced separability of grayscale intensities, outperformed the other methods in automation, and was successful in isolating fractures from the porous rock matrix. Because the other methods are more likely to misclassify fracture edges as void and/or have limited capacity in distinguishing fractures from pores, those methods estimated larger fracture volumes (up to 80 %), surface areas (up to 60 %), and roughness (up to a factor of 2). These differences in fracture geometry would lead to significant disparities in hydraulic permeability predictions, as determined by 2D flow simulations.