Transport and Retention of Concentrated Oil-in-Water Emulsions in

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Remediation and Control Technologies

Transport and Retention of Concentrated Oil-in-Water Emulsions in Porous Media Katherine A. Muller, Somayeh G Esfahani, Steven C. Chapra, and C. Andrew Ramsburg Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b06012 • Publication Date (Web): 09 Mar 2018 Downloaded from http://pubs.acs.org on March 9, 2018

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Environmental Science & Technology

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Transport and Retention of Concentrated Oil-in-Water Emulsions in Porous Media

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Katherine A. Mullera,b*, Somayeh G. Esfahania,c, Steven C. Chapraa, C. Andrew Ramsburga a

Department of Civil and Environmental Engineering, Tufts University, 200 College Avenue, Room 113, Anderson Hall, Medford, Massachusetts, USA b

Current affiliation: Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee c

Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Texas, USA *

corresponding author

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For Submission To:

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Environmental Science and Technology

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March 2018

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TOC/ABSTRACT ART

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ABSTRACT Oil-in-water emulsions are routinely used in subsurface remediation with most applications

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utilizing highly concentrated emulsions (i.e., ≥ 20% wt.). These high oil loadings present a

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challenge to remedial design as mechanistic insights into transport and retention of concentrated

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emulsions is limited. Column experiments were designed to examine emulsion transport and

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retention over a range of input concentrations (1.3 - 23% wt.). Droplet breakthrough and

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retention data from low concentration experiments was successfully described by existing

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particle transport models. These models, however, failed to capture droplet transport in more

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concentrated systems. At high oil fraction, breakthrough curves exhibited an early fall at the end

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of the emulsion pulse and extending tailing. Irrespective of input concentration, all retention

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profiles displayed hyper-exponential behavior. Here, we extended existing model formulations to

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include the additional mixing processes occurring when at high oil concentrations - with focus on

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the influence of deposited mass and viscous instabilities. The resulting model was parameterized

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with low concentration data and can successfully predict concentrated emulsion transport and

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retention. The role of retained mass and viscous instabilities on mixing conditions can also be

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applied more broadly to systems with temporal or spatially variant water saturation or when

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viscosity contrasts exist between fluids.

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INTRODUCTION

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Oil-in-water emulsions have been used in environmental remediation for a variety of

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applications including: enhanced contaminant recovery (e.g.,1-2); contaminant stabilization (e.g.,

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ingredients to the subsurface (e.g.,10-12). Utilization of emulsions for in situ remediation requires

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a balance between retention of remedial amendments and ease of introducing and distributing the

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amendment in the subsurface. Concentrated emulsions (e.g., in excess of 10% wt. dispersed

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phase content) or neat edible oils can be used to reach remediation outcomes 4, 6, 13. However,

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emulsion transport and retention, especially at high concentration, remains largely empirical.

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Remediation design can be improved through a greater emphasis on the processes controlling

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emulsion mobility and retention in porous media.

) fermentable substrate delivery (e.g.,4-6); mobility control (e.g.,7-9); and to deliver active

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A critical aspect of emulsion transport modeling is the need to incorporate changes to the

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droplet retention characteristics over the course of a retention event (e.g., through a reduction of

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the filter coefficient 14, introduction of surface capacity 15-16, or conceptualization of film flow

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component 17). The influence of input concentration, emulsion viscosity, and droplet retention on

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mixing and tailing is largely absent in emulsion transport models, despite observations of

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emulsion tailing (e.g.,15, 18-19). Increased colloid mobility with increasing input concentration has

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been demonstrated within the colloid literature, yet the influence of input concentration in the

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emulsion literature is limited. Neglecting input concentration is particularly troubling, given that

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droplet concentration (or oil fraction) can cause emulsion viscosities to vary over orders of

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magnitude. For example, Soo & Radke 14 exclude emulsions greater than 1% from their

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modeling effort, and Coulibaly et al.15 suggest degraded model performance when emulsion

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density and viscosity deviate from that of water.

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Viscosity contrasts between invading and resident fluids, regardless of miscibility, can

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result in flow instabilities. Specifically, conditions are favorable for viscous fingering when a

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less viscous fluid displaces a more viscous fluid 20. This is a relevant, but often overlooked,

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aspect of amendment delivery, as groundwater re-enters a treatment zone following a period of

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amendment injection (amendments have viscosities greater than that of water). The resulting

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instability may or may not be negligible. But, the influence of viscous fingering on transport

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during miscible displacements such as those experienced during concentrated emulsion delivery, 4 ACS Paragon Plus Environment

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needs to be accounted for using averaged models or direct numerical simulations of the physical

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fingering process (e.g., 20-21). Viscous fingering degrades the applicability of standard

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mechanical dispersion assumptions 22; however, when the dispersed phase is conceptualized as a

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solute (as in colloid filtration theory), viscous instabilities can manifest as dispersive mixing 22.

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The overall objective of this work was to explore the role of input droplet concentration

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on emulsion transport and retention. Specifically, we aimed to develop a modeling approach that

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captures the influence of droplet concentration on droplet transport. This was accomplished by:

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(i) understanding the roles of mass retention and viscosity contrasts on emulsion transport in

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sandy porous media, and (ii) ascertaining if incorporating these effects enables prediction of high

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concentration (i.e., 20-25% wt.) emulsion transport using colloid-filtration models parameterized

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at low concentration (i.e., 1.3-2.3% wt.).

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MATERIALS AND METHODS

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Materials. Soybean oil (SBO, MP Biomedicals, Laboratory grade), Gum Arabic (GA,

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>99% purity), sodium bromide (NaBr, 99.9% purity, ACS grade), and sodium chloride (NaCl,

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99.5% purity, ACS grade) were purchased from Fisher Scientific. High purity water, denoted

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MilliQ water, (resistivity > 18.2 mΩ-cm and total organic carbon E ⋅ H

(4)

−1

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All terms in Equation 4 other than L, the column length [L], have been previously defined. The

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functional form of Equation 4 is similar to that used by Flowers and Hunt 22 to describe the

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mixing effects of fingering in miscible displacements of brines.

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RESULTS AND DISCUSSION

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Emulsion Properties. The GA-stabilized oil-in-water emulsions used herein had

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dispersed phase contents between 1 and 25% wt. Emulsion charactersitics include a d50 between

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1.0 and 1.5 µm, zeta potentials from -30 and -35 mV, densities between 0.992 and 0.998 g/mL,

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and viscosities between 1 and 10 mPa·s. Emulsion density varied less than 0.6% across

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approximately an order of magnitude of dispersed phase content. This suggests that the phase

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density of these emulsions can be assumed to be independent of the amount of deposition

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occuring during transport or the influent emulsion content (i.e., temporal and spatial derivitatives

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of phase density can be assumed to be zero). In constrast, emulsion viscosity varies by an order

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of magnitude over the same range of dispersed phase content, suggesting viscous instabilities

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may influence emulsion transport (i.e., mobility ratio greater than 1). 12 ACS Paragon Plus Environment

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Emulsion Retention. When considering retention on FF sand (i.e., experiments 1-4), the

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influence of emulsion concentration is clear. Dilute emulsions (1.3 & 2.3% dispersed phase)

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were found to retain between 2 and 8 mg DP·g-sand-1. In contrast, retention of the concentrated

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emulsion (23% dispersed phase content) was found to be between 20 and 50 mg DP·g-sand-1. In

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all cases the dispersed phase retention was characterized by a hyper-exponential pattern (Figure

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1, Table S2).

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Figure 1. Experimental dispersed phase breakthrough curves (left) and retention profiles (right)

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for experiments 1A and 1B (a,b); experiments 2A & 2B (c,d); and experiments 3A, 3B, and 4


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(e,f). Note the change in y-axis of (b) & (d) compared to (f). The influence of mass deposition on

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water saturation is shown in the Supporting Information (Figure S2).

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Dispersivity. Dispersion was found to increase by an order-of-magnitude between the

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pre- and post-emulsion tracer tests and could not be accounted for through velocity alone (i.e.,

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changes in velocity relating to the decreased water saturation in the porous medium). Recall that

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the distribution of retained emulsion droplets was spatially non-uniform (i.e., hyper-exponential

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deposition). Rather than masking this non-uniformity in a single value of dispersivity for the

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entire column, we explored both linear and nonlinear formulations linking mechanical mixing to

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emulsion retention.



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Figure 2. Non-reactive tracer test results before (left) and after (right) emulsion injection. (a)

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Pre-injection and (b) Post-injection tracer tests with corresponding constant, linear, and

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nonlinear models for experiment 1 (c) Pre-injection and (d) Post-injection tracer tests for

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experiment 3 (e) Pre-injection and (f) Post-injection tracer tests for experiment 4.

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Fits of each Dm model to experiments 1 and 3 suggest that both the linear (AICc = -155.1) and nonlinear (AICc = -156.5) models provide very similar value in describing the non-reactive 16 ACS Paragon Plus Environment

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tracer transport (Figure 2). Moreover, model parameters fit to data from experiments 1 and 3

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(M1=19.6; M2=37.6, N=1.26) provide good predictions for the post-emulsion tracer data obtained

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from experiment 4 (which was conducted at high input concentration and independent of those

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used in the fitting). Based on the slightly lower AICc, the nonlinear expression was selected for

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use throughout this work (Figure 2f).

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Emulsion Transport. Results from experiment 1 (1.3 % wt.) show a rise across the ‘top’

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of the breakthrough curves (BTCs) and hyper-exponential retention profiles (RPs) (Figure 1 a-b).

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While the RPs in experiment 2 (2.3% wt.) are also hyper-exponential, the rise in the BTCs

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appears more muted and rounded (Figure 1 c-d). Results from experiment 3 (23% wt.) also show

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hyper-exponential retention, but the influence of retention on the BTC appears limited. More

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noticeable in the BTC are the approach of the effluent concentration to that of the influent, an

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early fall of the emulsion pulse (i.e., early breakthrough of the post-emulsion flush), and

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pronounced emulsion tailing. Remobilization of the retained mass was found to be insignificant

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even after periods of extended flushing (data not shown).

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The fraction of mass retained in experiments 1, 2 and 3 was approximately 0.33, 0.25,

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and 0.17, respectively. While these fractions and the BTCs appear to suggest an increasingly

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more limited role of retention with increasing influent concentration, there is substantial mass

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retained in all cases, and retention is greater when higher dispersed phase content is input (Figure

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1). At lower influent concentrations (experiments 1 and 2), maximum retention is

Transport and Retention of Concentrated Oil-in-Water Emulsions in

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