Multiphase and multicomponent simulation of acid mine drainage in unsaturated mine waste: Modeling approach, benchmarks and application examples

Muniruzzaman, Muhammad; Karlsson, Teemu; Ahmadi, Navid; Rolle, Massimo

doi:10.1016/j.apgeochem.2020.104677

Cited by 23 publications

(10 citation statements)

References 103 publications

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“…Besides remediation applications, the proposed approach combining process-based, multi-physics and multicomponent reactive transport modeling with response surface surrogate modeling, could be adopted in other fields of subsurface research including radioactive waste confinement (Montes-H et al, 2005;Tournassat et al, 2015), CO 2 storage (Celia et al, 2015;Gislason et al, 2010;Saaltink et al, 2013), multiphase and unsaturated flow systems (Ahmadi et al, 2020;Molins & Mayer, 2007), as well as mining operations and risk assessments (Martens et al, 2021;Muniruzzaman et al, 2020;Sinclair & Thompson, 2015).…”

Section: Discussionmentioning

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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Section: Discussionmentioning

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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“…The rapid development of numerical models was promoted on the one hand by the increasingly high power and low costs of computational machines, and on the other hand by the increasing awareness of the importance of embedding heterogeneities for model predictions (heterogeneity is hardly embedded into analytical solutions). Nowadays, multiphase multicomponent reactive transport models are able to simulate a wide range of processes, including both advective and diffusive gas transport, the effects of oxidizing agents in contact with sulfidic materials and the interaction between minerals and pore-fluids (da Silva et al 2009;Ma et al 2019;Mayer et al 2015;Molson et al 2005;Muniruzzaman et al 2020;Sracek et al 2004;Wang et al 2019).…”

Section: First Modelsmentioning

confidence: 99%

“…For instance, when adopting codes from the family of geochemical code PHREEQC (Parkhurst and Appelo 2013), two new modules, IPhreeqc (Charlton and Parkhurst 2011) and PhreeqcRM (Parkhurst and Wissmeier 2015) are specifically designed to access PHREEQC's reaction capabilities from any scripting languages. This facilitates a faster communication between the geochemical code and transport simulators without the need of reading/writing external files (Muniruzzaman et al 2020;Rolle 2016, 2019;Rolle et al 2018;Sprocati et al 2019).…”

Section: ''Hybrid'' Approachesmentioning

confidence: 99%

Mechanistic models supporting uncertainty quantification of water quality predictions in heterogeneous mining waste rocks: a review

Muniruzzaman

Pedretti

2020

Stoch Environ Res Risk Assess

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Polluted drainage from weathering of sulfide-rich waste rock deposits can cause long-term impairment to waterways and biodiversity near mining sites. Mechanistic models represent established tools to support the predictions of the quantity and quality of waste rock drainage, and their associated risks. Yet, model-based predictions in typical waste rock systems are ubiquitously uncertain because of the strongly heterogeneous nature of these waste deposits. Embedding heterogeneity within predictive modeling is complicated by the magnitude and level of knowledge of the waste rock heterogeneity, and the large number of scale-dependent parameters feeding the model equations. This review encompasses deterministic and stochastic modeling approaches that emphasize consolidated tools and emerging modeling solutions to deal with heterogeneity for the modeling of waste rocks. Physical (e.g., variability of texture, hydraulic and pneumatic properties), geochemical (e.g., variability of mineralogy and kinetic parameters), and thermal heterogeneities are evaluated. The review points out the importance of stochastic modeling as a fundamental approach to embed uncertainty in long-term model-based decisions. Regulators and decision makers must be convinced of the benefit of using stochastic modeling, which is still considered to belong mainly to the academic sphere.

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“…Although the dissolution of As-bearing sulfide minerals occurs naturally in the subsurface, anthropogenic activities can exacerbate this contamination by enhancing the exposure of sulfide minerals to oxygen. For instance, the disposal of mine tailings and their exposure to atmospheric oxygen is known to potentially result in the generation of acid mine drainage, triggering the dissolution of a variety of mineral phases and the mobilization of contaminants. − Managed aquifer recharge (MAR) can also enhance arsenic release in groundwater from the dissolution of sulfide minerals naturally present in the subsurface due to the direct injection of oxic water in the subsurface. − Furthermore, seasonal fluctuation in water level and hydraulic fracturing have been shown to increase the exposure of sulfide minerals to atmospheric O 2 and, consequently, to enhance their dissolution. Thus, detailed understanding of the geochemical and hydrological processes controlling the dissolution of these As-bearing minerals is fundamental for the adequate understanding of natural and engineering systems and for improved management of groundwater resources.…”

Section: Introductionmentioning

confidence: 99%

Oxidative Dissolution of Arsenic-Bearing Sulfide Minerals in Groundwater: Impact of Hydrochemical and Hydrodynamic Conditions on Arsenic Release and Surface Evolution

Stolze

Battistel

Rolle

2022

Environ. Sci. Technol.

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The dissolution of sulfide minerals can lead to hazardous arsenic levels in groundwater. This study investigates the oxidative dissolution of natural As-bearing sulfide minerals and the related release of arsenic under flow-through conditions. Column experiments were performed using reactive As-bearing sulfide minerals (arsenopyrite and lollingite) embedded in a sandy matrix and injecting oxic solutions into the initially anoxic porous media to trigger the mineral dissolution. Noninvasive oxygen measurements, analyses of ionic species at the outlet, and scanning electron microscopy allowed tracking the propagation of the oxidative dissolution fronts, the mineral dissolution progress, and the change in mineral surface composition. Process-based reactive transport simulations were performed to quantitatively interpret the geochemical processes. The experimental and modeling outcomes show that porewater acidity exerts a key control on the dissolution of sulfide minerals and arsenic release since it determines the precipitation of secondary mineral phases causing the sequestration of arsenic and the passivation of the reactive mineral surfaces. The impact of surface passivation strongly depends on the flow velocity and on the spatial distribution of the reactive minerals. These results highlight the fundamental interplay of reactive mineral distribution and hydrochemical and hydrodynamic conditions on the mobilization of arsenic from sulfide minerals in flow-through systems.

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Multiphase and multicomponent simulation of acid mine drainage in unsaturated mine waste: Modeling approach, benchmarks and application examples

Cited by 23 publications

References 103 publications

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

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

Mechanistic models supporting uncertainty quantification of water quality predictions in heterogeneous mining waste rocks: a review

Oxidative Dissolution of Arsenic-Bearing Sulfide Minerals in Groundwater: Impact of Hydrochemical and Hydrodynamic Conditions on Arsenic Release and Surface Evolution

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