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• A 2D facility is developed for simulating groundwater remediation by ozone MNBs. • MNBs can migrate over long distances with high dispersion. • Organics-contaminated groundwater can be effectively remediated by ozone MNBs. Ozone micro-nano-bubbles (MNBs) enhanced oxidation is a promising in-situ remediation technology for organics-contaminated groundwater. The transport behavior of MNBs and contaminant removal effect in actual groundwater scene is not yet comprehensively understood, although one-dimensional column experiments and batch tests were conducted to investigate the migration of MNBs and contaminant degradation in previous studies. Here, a novel two-dimensional (2D) physical modeling facility was developed, which can characterize the tempo-spatial distribution of MNBs and contaminant in groundwater. The facility was used to explore the migration of MNBs under different hydraulic gradients and the removal of methyl orange, a representative organic pollutant, using ozone MNBs. The experimental results show that groundwater flow velocity has a significant influence on the migration behavior of MNBs. A model including groundwater flow, MNBs transport, and dissolved gas transport can well capture the migration and distribution of MNBs under different hydraulic gradients. The longitudinal and transverse dispersivities of the MNBs were calculated to be 1.14 cm and 0.18 cm, respectively. MNBs are able to migrate with groundwater flow to long distances and exhibit strong dispersion in the lateral and longitudinal directions. The increase in hydraulic gradient greatly enhances the transport of MNBs in groundwater and relieves the deposited MNBs on the surface of porous media. At a hydraulic gradient increasing from 0.033 to 0.1, the range of influence of MNBs increased from about 80 cm × 40 cm to 140 cm × 39 cm after 36 h of injection of oxygen MNBs water. The methyl orange in groundwater is effectively removed by ozone MNBs enhanced oxidation, showing the remarkable remediation ability of ozone MNBs. The area of influence and pollutant removal of the ozone MNBs expanded with injection, and the area of influence was approximately 48 cm × 30 cm after 48 h of treatment. We also discuss the effect of groundwater matrix on ozone MNB migration and degradation of contaminants. The 2D model tests illustrate the mechanism of MNB migration and indicate that ozone MNBs enhanced oxidation technology has great potential in the remediation of organics-contaminated groundwater. [ABSTRACT FROM AUTHOR]

The nitrogen sorption isotherm is conventionally used to deduce the specific surface area of porous materials. However, it often exhibits a sharp drop around 0.5 relative pressure. A theory explicitly accounting for intermolecular-scale pressure, instead of classical theories of constant disjoining pressure in condensed liquid, is constructed and used to determine cavitation during desorption. Intermolecular-scale liquid pressure distribution is quantified using a recently developed soil sorptive potential framework, showing compressive liquid nitrogen pressure decaying nonlinearly with increasing distance to the particle surface. A range of cavitation pressure is predicted by classical nucleation theory and the van der Waals equation of state. Cavitation is shown to be triggered when nitrogen's global minimum liquid pressure falls within the cavitation threshold. It is shown that this criterion is valid for all tested soils. Computed minimum liquid pressure always occurs at 0.5 relative pressure, which is in accordance with experimental isotherm data and further indicates the validity of the cavitation onset criterion. [ABSTRACT FROM AUTHOR]

Colloid transport and retention in porous media is a common phenomenon in both nature and industry. However, many questions remain on how to obtain colloid transport and retention parameters. Previous work usually assumed constant transport parameters in a medium under a given physicochemical condition. In this study, pore‐network modeling is employed to upscale colloid transport and retention from the pore‐scale to the macro‐scale. The pore‐scale transport parameters including the collection efficiency (η), the sticking efficiency (α), and the fraction of the solid‐water interface that contributes to the colloid attachment (Sf) are obtained using numerical simulation and probability analysis for each pore throat. The influence of roughness and charge heterogeneity on the distribution of pore‐scale parameters is discussed. Breakthrough curves and the retention profiles under different roughness and charge heterogeneity conditions are also analyzed. Results show that pore‐scale parameters η, α, and Sf have various distributions in porous media that may not be accurately described using single‐valued effective parameters. The value of η decreases with velocity and exhibits a wide distribution under low‐velocity conditions. The parameter α tends to decrease with the colloid size and the pore water velocity and increased with the charge heterogeneity fraction. Nanoscale roughness alters α in a non‐monotonic fashion but tends to increase for lower roughness fractions and zeta potential. Microscopic roughness increases values of α for colloids that would otherwise be susceptible to hydrodynamic removal. Breakthrough curves and retention profiles show that more retention occurs for smaller particles, which reflects the influence of blocking. Key Points: Pore‐network modeling is employed to upscale colloid transport and retention from the pore‐scale to the macro‐scaleThe nanoscale roughness, charge heterogeneity, and microscopic roughness have an obvious impact on colloid transport and retentionPore‐scale parameters for different pore throats in the porous media have various distribution [ABSTRACT FROM AUTHOR]

• A neural-network model is trained to predict collector contact efficiency of each pore throat (η t). • Influence of pore structure of porous media is described by pore network models, where the η t occurs as a distribution. • Upscaled values of the deposition rate coefficient are provided by PNMs and compared with the prediction of colloid filtration theory. • High velocity region of flow field neglected in colloid filtration theory leads to the difference in the prediction of deposition rate coefficient. Conventional colloid filtration theory (CFT) uses the single collector contact efficiency (η) to describe the mass transfer of colloids to a collector surface. However, this approach neglects the full complexity of the pore structure and flow field of real porous media. In this study, the porous medium geometry, flow field, and colloid mass transfer are quantified using a pore-network model (PNM). A database of pore scale η is established by finite-element method to train a Neural-network model (NNM). The reasonable prediction of η indicates the potential of using the developed NNMs as an alternative to correlation equations, which can free the users from repeated numerical simulation. In contrast to the prediction by conventional CFT, the value of η in the PNM occurs as a distribution, which is dependent upon the geometry parameters of the PNM. The mean value of η increases with the standard deviation of pore radius and decreases with the curvature number, but the dependency on coordination number is more complex. Upscaled values of the deposition rate coefficient (k d) corresponding to the distribution of η are calculated by the breakthrough curves by PNMs. The prediction of k d by PNM is then compared with that by CFT. Results show that k d predicted by PNM shows more significant response to velocity change, and less remarkable response to colloid density change than k d predicted by CFT. The comparison between the flow velocity distribution between PNM and CFT shows that the high-velocity region of the flow field in the porous media has been neglected in CFT, which can lead to insufficient consideration of convection. The results of this work imply that it is necessary to consider the influence of the complex pore structure of porous media on the collection of colloids. [ABSTRACT FROM AUTHOR]

SUMMARY Air sparging (AS) is an in situ soil/groundwater remediation technology, which involves the injection of pressurized air/oxygen through an air sparging well below the zone of contamination. Characterizing the mechanisms governing movement of air through saturated porous media is critical for the design of an effective cleanup treatment system. In this research, micromechanical investigation was performed to understand the physics of air migration and subsequent spatial distribution of air at pore scale during air sparging. The void space in the porous medium was first characterized by pore network consisting of connected pore bodies and bonds. The biconical abscissa asymmetric concentric bond was used to describe the connection between two adjacent pore bodies. Then a rule-based dynamic two-phase flow model was developed and applied to the pore network model. A forward integration of time was performed using the Euler scheme. For each time step, the effective viscosity of the fluid was calculated based on fractions of two phases in each bond, and capillary pressures across the menisci was considered to compute the pressure field. The developed dynamic model was used to study the rate-dependent drainage during air sparging. The effect of the capillary number and geometrical properties of the network on the dynamic flow properties of two-phase flow including residual saturation, spatial distribution of air and water, dynamic phase transitions, and relative permeability-capillary pressure curves were systematically investigated. Results showed that all the above information for describing the air water two-phase flow are not intrinsic properties of the porous medium but are affected by the two-phase flow dynamics and spatial distribution of each phase, providing new insight to air sparging. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Air sparging is an in situ soil/groundwater remediation technology, which involves the injection of pressurized air through air sparging well below the zone of contamination. To investigate the rate-dependent flow properties during multistep air sparging, a rule-based dynamic two-phase flow model was developed and applied to a 3D pore network which is employed to characterize the void structure of porous media. The simulated dynamic two-phase flow at the pore scale or microscale was translated into functional relationships at the continuum-scale of capillary pressure-saturation ( P- S) and relative permeability-saturation ( K- S) relationships. A significant contribution from the air injection pressure step and duration time of each air injection pressure on both of the above relationships was observed during the multistep air sparging tests. It is observed from the simulation that at a given matric potential, larger amount of water is retained during transient flow than that during steady flow. Shorter the duration of each air injection pressure step, there is higher fraction of retained water. The relative air/water permeability values are also greatly affected by the pressure step. With large air injection pressure step, the air/water relative permeability is much higher than that with a smaller air injection pressure step at the same water saturation level. However, the impact of pressure step on relative permeability is not consistent for flows with different capillary numbers ( N). When compared with relative air permeability, relative water permeability has a higher scatter. It was further observed that the dynamic effects on the relative permeability curve are more apparent for networks with larger pore sizes than that with smaller pore sizes. In addition, the effect of pore size on relative water permeability is higher than that on relative air permeability. [ABSTRACT FROM AUTHOR]

• Colloids transport and retention are simulated by pore network model. • Surface deposition, hydrodynamic bridging and straining are included in PNM. • Hydrodynamic bridging and straining produce hyper-exponential retention profiles. • The impact of hydrodynamic bridging increases with colloid size, initial concentration, and flow velocity. Colloid transport and retention in porous media is a common phenomenon in nature. However, retention mechanisms are not fully revealed based on macroscale experimental observations. The pore-network model (PNM) is an effective method to account for the pore structure of a porous medium and provides a direct connection between pore-scale retention mechanisms and macroscale phenomenon. In this study, PNMs with cylindrical pore throats and spherical pore bodies are used to upscale water flow and colloid transport from pore- to macro-scales, taking into consideration surface deposition, hydrodynamic bridging, and straining. Numerical experiments were conducted to investigate the effect of colloid size, initial concentration, and flow velocity of pore water on colloid transport and retention behavior. Results show that hydrodynamic bridging and straining produce hyper-exponential retention profiles, whereas surface deposition due to nanoscale roughness and charge heterogeneity yields exponential or uniform retention profiles. Hydrodynamic bridging will not happen when the colloid size, initial concentration and flow velocity are lower than some threshold value (r p ≤ 500 nm, C 0 ≤ 7.1 × 1014 Nc/m3, U 0 ≤ 0.1 m/d under the conditions of this study). The relative importance of hydrodynamic bridging in comparison to surface deposition increases with an increase in the colloid size, initial concentration, and flow velocity. The PNM is a useful tool to discriminate different retention mechanisms and to predict colloid transport and retention behavior in porous media. [ABSTRACT FROM AUTHOR]

• Pore- and macroscale colloid sticking efficiency (α t and α M) is determined by pore-network model. • Energy and torque balances are calculated throughout the spatial pore structure to determine the distribution of α t. • Geochemical environment and pore surface characteristics control the sticking of smaller colloids due to impact on interaction energies. • Hydrodynamic conditions play an eventually dominant role in determining α t for larger colloids. The sticking efficiency (α) is a vital parameter to predict the transport and deposition of colloids in porous media. The value of α depends on various factors such as the interaction energy between colloids and the solid-water interface (SWI), kinetic energy fluctuations of diffusing colloids, and the hydrodynamics of the flow field in the pore structure. However, α is usually assumed to be spatially constant and fitted from experimental data. In this study, a theoretical method is proposed to predict the distribution of the sticking efficiency at pore scale (α t) using a pore network model (PNM) and the macroscale sticking efficiency of the whole porous media (α M) by means of upscaling. A PNM is established to simulate the pore structure of porous media and to obtain the flow field, and energy and torque balances are calculated throughout the spatial pore structure to determine the distribution of α t under different physiochemical conditions. The value of α M is determined through breakthrough curves provided by the PNM under favorable and unfavorable conditions. Results show the distribution of α t is sensitive to various factors including colloid characteristics, pore surface features, geochemical environment and hydrodynamic conditions. Colloid characteristics like colloid surface zeta potential, geochemical environment such as solution ionic strength, and pore surface characteristics including nanoscale roughness and especially charge heterogeneity have a controlling influence on α t for nanoparticles (<100 nm) due to their impact on interaction energies. Hydrodynamic conditions played an increasingly important and eventually dominant role in determining α t for larger colloids by changing the sticking of weakly associated colloids (e.g., at secondary minima). When hydrodynamic torques are weak, the influence of colloid size on α t can be non-monotonic due to the combined influence of interaction energy and hydrodynamic torques. As a result, higher values of α M occurred for smaller colloid sizes, lower flow velocities, larger pore sizes, and in the presence of microscopic roughness. The method proposed by this study can be used to predict the sticking efficiency under different solution and solid phase chemistries, nanoscale heterogeneities, microscopic roughness, flow velocities, and pore structure conditions. [ABSTRACT FROM AUTHOR]