Process-based modeling of electrokinetic-enhanced bioremediation of chlorinated ethenes

Sprocati, Riccardo; Flyvbjerg, John; Tuxen, Nina; Rolle, Massimo

doi:10.1016/j.jhazmat.2020.122787

Cited by 19 publications

(15 citation statements)

References 85 publications

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Section: Eof Through Nanoscale Pores and Channelsmentioning

confidence: 99%

“…The two transport mechanisms shown here are (I) electromigration and (II) electroosmosis. The figure has been reprinted from [165].…”

Section: Eof Through Nanoscale Pores and Channelsmentioning

confidence: 99%

“…48). A mechanistic understanding of the multidimensional transport of organic and inorganic contaminants coupled with the reactions in porous media has drawn attention recently [165][166][167]. In this regard, Sprocati et al [166] modeled the electrokinetic transport with biogeochemical reactions in porous media for continuum scale by combining COMSOL Multiphysics and PhreeqcRM.…”

Section: Eof Through Nanoporous Mediamentioning

confidence: 99%

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Electroosmotic flow: From microfluidics to nanofluidics

et al. 2021

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Electroosmotic flow (EOF), a consequence of an imposed electric field onto an electrolyte solution in the tangential direction of a charged surface, has emerged as an important phenomenon in electrokinetic transport at the micro/nanoscale. Because of their ability to efficiently pump liquids in miniaturized systems without incorporating any mechanical parts, electroosmotic methods for fluid pumping have been adopted in versatile applications—from biotechnology to environmental science. To understand the electrokinetic pumping mechanism, it is crucial to identify the role of an ionically polarized layer, the so‐called electrical double layer (EDL), which forms in the vicinity of a charged solid–liquid interface, as well as the characteristic length scale of the conducting media. Therefore, in this tutorial review, we summarize the development of electrical double layer models from a historical point of view to elucidate the interplay and configuration of water molecules and ions in the vicinity of a solid–liquid interface. Moreover, we discuss the physicochemical phenomena owing to the interaction of electrical double layer when the characteristic length of the conducting media is decreased from the microscale to the nanoscale. Finally, we highlight the pioneering studies and the most recent works on electro osmotic flow devoted to both theoretical and experimental aspects.

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Section: Eof Through Nanoscale Pores and Channelsmentioning

confidence: 99%

“…The two transport mechanisms shown here are (I) electromigration and (II) electroosmosis. The figure has been reprinted from [165].…”

Section: Eof Through Nanoscale Pores and Channelsmentioning

confidence: 99%

Section: Eof Through Nanoporous Mediamentioning

confidence: 99%

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Electroosmotic flow: From microfluidics to nanofluidics

et al. 2021

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“…The process‐based model used in this study accounts for fast, equilibrium reactions for aqueous speciation and kinetically controlled reactions for contaminant biodegradation and microbial population dynamics. In the proposed conceptual model, lactate is used as electron donor by both indigenous OHRB and bioaugmented OHRB (KB‐1) (Duhamel & Edwards, 2007; Sprocati et al., 2020) to degrade PCE to TCE, DCE, VC, and ethene. The general microbially mediated redox reaction for the first step of PCE degradation to TCE using lactate as electron donor reads as:

\frac{1}{6} {normalC}_{3} {normalO}_{5} {normalH}_{3}^{-} + {normalC}_{2} {Cl}_{4} + {normalH}_{2} O \to {normalC}_{2} H C {normall}_{3} + C {normall}^{-} + \frac{4}{3} {normalH}^{+} + \frac{1}{2} H C {normalO}_{3}^{-}

…”

Section: Modeling Approachmentioning

confidence: 99%

Integrating Process‐Based Reactive Transport Modeling and Machine Learning for Electrokinetic Remediation of Contaminated Groundwater

Sprocati

Rolle

2021

Water Resources Research

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Advanced reactive transport models of fluid flow and solute transport in subsurface porous media are instrumental for the assessment of contaminant environmental fate and for the design of in situ remediation interventions. However, the increasing complexity of process‐based reactive transport simulators often leads to long runtimes, which poses severe restrictions for tasks that require numerous model evaluations. To overcome this limitation, we demonstrate how machine learning surrogate models, trained on the outputs of a limited number of process‐based reactive transport simulations, can predict the evolution of complex subsurface systems. We focus on electrokinetic enhanced bioremediation of chlorinated solvents in low‐permeability porous media, which is an in situ remediation technology entailing a suite of complex and coupled physical, chemical, and biological processes. A process‐based, multicomponent reactive transport model, capable of describing the key mechanisms of electrokinetic flow and transport, is setup in a two‐dimensional domain. The model accounts for electromigration and electroosmosis, the electrostatic interactions between charged species, the chemistry of the pore water solution, the microbially mediated degradation of the organic compounds, and the dynamics of different degraders. We develop a response surface surrogate framework using an artificial neural network as approximation function and we show that the surrogate model has the capability and the flexibility to capture the complex dynamics of electrokinetic remediation in subsurface porous media and allows computationally efficient model exploration, sensitivity analysis, and uncertainty quantification.

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“…Such profiles were evaluated both from the pictures, using a calibration function relating the color intensity to the tracer concentration, and from the outcomes of a 2-D forward model, describing the physical and electrostatic processes in the setup 36,37,39 . The simulation results,…”

Section: Conservative Transport Experimentsmentioning

confidence: 99%

Electrokinetic Delivery of Reactants: Pore Water Chemistry Controls Transport, Mixing, and Degradation

Sprocati

Gallo

Sethi

et al. 2020

Environ. Sci. Technol.

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Process-based modeling of electrokinetic-enhanced bioremediation of chlorinated ethenes

Cited by 19 publications

References 85 publications

Electroosmotic flow: From microfluidics to nanofluidics

Electroosmotic flow: From microfluidics to nanofluidics

Integrating Process‐Based Reactive Transport Modeling and Machine Learning for Electrokinetic Remediation of Contaminated Groundwater

Electrokinetic Delivery of Reactants: Pore Water Chemistry Controls Transport, Mixing, and Degradation

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