Acid Erosion of Carbonate Fractures and Accessibility of Arsenic-Bearing Minerals: In Operando Synchrotron-Based Microfluidic Experiment

Abstract

Underground flows of acidic fluids through fractured rock can create new porosity and increase accessibility to hazardous trace elements such as arsenic. In this study, we developed a custom microfluidic cell for an in operando synchrotron experiment using X-ray attenuation. The experiment mimics reactive fracture flow by passing an acidic fluid over a surface of mineralogically heterogeneous rock from the Eagle Ford shale. Over 48 h, calcite was preferentially dissolved, forming an altered layer 200–500 μm thick with a porosity of 63–68% and surface area >10× higher than that in the unreacted shale as shown by xCT analyses. Calcite dissolution rate quantified from the attenuation data was 3 × 10–4 mol/m2s and decreased to 3 × 10–5 mol/m2s after 24 h because of increasing diffusion limitations. Erosion of the fracture surface increased access to iron-rich minerals, thereby increasing access to toxic metals such as arsenic. Quantification using XRF and XANES microspectroscopy indicated up to 0.5 wt % of As­(-I) in arsenopyrite and 1.2 wt % of As­(V) associated with ferrihydrite. This study provides valuable contributions for understanding and predicting fracture alteration and changes to the mobilization potential of hazardous metals and metalloids.

Microfluidics as an Emerging Platform for Exploring Soil Environmental Processes: A Critical Review

“…Although this discrepancy in dissolution rates may not be a general phenomenon and is likely to be controlled by the mineral structures, microfluidic experiments can provide nonequilibrium dynamic dissolution (and adsorption) information and reveal the potential effects of microenvironments. Recently, Deng et al coupled the microfluidic cell with synchrotron-based X-ray attenuation measurements . They characterized the elemental changes during acid erosion of carbonate fractures and revealed the exposure of embedded Fe–As with the possibility of mobilization.…”

“…Currently, optical and fluorescent imaging are the commonest on-chip monitoring methods. , There is a need to develop other on-chip quantitative measurement methods, such as chemical probes for selective imaging of species, integrated microelectrodes, and planar optodes . It is also necessary to explore how to integrate microfluidics with mainstream and novel characterization techniques that are used for probing soil interfacial chemistry, such as spectroscopy (including UV–vis, Raman, infrared), ,, synchrotron-based techniques, , atomic force microscopy, and secondary ion mass spectrometry . In these ways, both aqueous and interfacial chemical information can be acquired in situ on microfluidic platforms.…”

Investigation of Coupled Processes in Fractures and the Bordering Matrix via a Micro‐Continuum Reactive Transport Model

“…Recent advances in microscopic characterization techniques and computational power have enabled considerations of reactive transport processes in heterogeneous fractured porous media at the pore‐scale (Deng et al., 2020; Molins, 2015; Singh et al., 2017). In pore‐scale models, such as the mesh based pore‐scale reactive transport model (Bultreys et al., 2016; Molins et al., 2014; Starchenko & Ladd, 2018), lattice Boltzmann method (LBM; Curti et al., 2019; Kang et al., 2010; Prasianakis et al., 2017), and smooth particle hydrodynamics (SPH; Tartakovsky et al., 2007, 2016), the interfaces between fluid and solid phases are explicitly resolved and the flow field reflects fine‐scale morphology.…”

Addressing Water and Energy Challenges with Reactive Transport Modeling

“…Rich data sets of thermodynamic properties, kinetic mechanisms and rate constants, and distributions of mineralogy and surface area at small scales, among others, generated through advances in molecular level modeling and probing techniques (e.g., microscopy and spectroscopy) are now also incorporated into RTMs (Tokunaga et al, 1998;Goldberg et al, 2007;Scheibe et al, 2009;Y. Wu et al, 2011;Viswanathan et al, 2012;Deng et al, 2016Deng et al, , 2020Beckingham et al, 2017).…”

“…These expanded capabilities make long-term predictions about system evolution that draw inferences from much shorter-term laboratory experiments possible with RTMs. This development of dynamic modeling capability has benefited enormously from the development of nonintrusive imaging techniques and 4D scanning (Deng et al, 2015(Deng et al, , 2020Voltolini and Ajo-Franklin, 2020). For instance, the RTM developed by Ling et al (2021) in this special issue is based on x-ray micro-computed tomography imaging, synchrotron micro x-ray fluoresence, and micro x-ray diffraction data from experimental studies.…”