# Injection of Zerovalent Iron Gels for Aquifer Nanoremediation: Lab Experiments and Modeling

^{1}

^{2}

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Materials

_{10}), 1.9 μm (d

_{50}), and 3.97 μm (d

_{90}) and are composed of iron (98.55%), oxygen (0.80%), carbon (0.03%), nitrogen (0.01%), and other impurities (0.61%). Their specific surface area per unit of solid volume is 3.16 × 10

^{−6}${\mathrm{m}}^{2}/{\mathrm{m}}^{3},$ and their density is 9760 $\mathrm{kg}/{\mathrm{m}}^{3}$. Guar gum and xanthan gum were both provided by Rantec Corporation (Ranchester, Wyoming, USA) in the form of dry powder. The carboxymethyl cellulose (CMC-2000) was supplied by CHEMPOINT (Maastricht, The Netherlands).

^{3}. Furthermore, to eliminate any residual impurities and colloids, the sand was cleaned through three cycles of washing and sonication with NaOH 0.1 M, tap water, and deionized water.

#### 2.2. Preparation of the mZVI Slurry

#### 2.3. Bulk and Porous Medium Rheology

^{−3}and 1 × 10

^{4}s

^{−1}by means of an Antoon Paar (Graz, Austria) rheometer (MCR302). The gel rheology inside the porous medium was instead characterized through the interpretation of 4 column transport tests (details about the tests are reported in the next section). The interpretation procedure, reported in Figure S1, provided one couple of shear rate and viscosity value for each column test. The graph representing these data represents the fluid rheogram in the porous medium.

#### 2.4. Column Transport Tests

- Pre-conditioning the porous medium with 5 pore volumes (PVs) of deionized water;
- Injecting 10 PVs of iron slurry.

#### 2.5. Radial Transport Test

- 2 PVs pre-conditioning with deionized water;
- 0.8 PVs of iron slurry injection.

#### 2.6. mZVI Transport Model in Radial Geometry

- First site expressing irreversible blocking dynamics: blocking is a physicochemical deposition mechanism that typically happens when particle-particle interactions are strongly repulsive. In this case, the already deposited particles prevent suspended ones from further attachment, and a porous medium saturation can be achieved. The particle deposition rate decreases with increasing ${S}_{Fe,i}$ and goes to zero when the saturation concentration of deposited particles, ${S}_{max}$, is reached [44,49,50].
- Second site expressing irreversible straining dynamics: straining is a physical deposition mechanism due to colloid trapping into small pore throats. Straining is likely to occur when the ratio between the size of the colloid and the sand grain is greater than, or close to, 0.5% [51,52]. In this study, a ${d}_{50,Fe}/{d}_{50,sand}$ of 0.68% was found, suggesting that straining might be a relevant deposition mechanism in this system.

## 3. Results

#### 3.1. Bulk and Porous Medium Rheology

^{−1}that corresponded to the radial model region close to the injection well, where the highest velocities were observed. Such low viscosity values limited the pressure increase during the mZVI injection in the subsoil, reducing the risk of porous medium fracturing and the consequential generation of preferential flow paths. The experimental rheogram of the shear-thinning gel (dots) was fitted against the Ostwald de Waele power-law model (solid line) with a good agreement (Figure 2b). The parameters k and n, obtained from the experimental data fitting, were, respectively, 0.22 Pa∙s

^{n}and 0.52.

#### 3.2. Column Transport Tests and Modeling

_{0}> 0.8). In particular, the concentration data analysis suggested the presence of two concurrent retention mechanisms within the sandy bed: (1) the sigmoidal shape of the breakthrough curves indicates that the particle deposition rate is decreasing over time because of saturation phenomena typical of a blocking deposition mechanism [56,57]; (2) the hyper-exponential shape of the concentration profiles, associated with a maximum outlet concentration lower than C

_{0}, can be instead ascribed to irreversible straining kinetics [45,58]. The kinetic coefficients determined for each test through the inverse fitting of the concentration data are reported in Table S2. A constant value, equal to 0.0027 g

_{Fe}/kg

_{Sand}, was found for the blocking parameter ${S}_{max}$, while a velocity-dependent behavior was observed for ${k}_{a,1}$, ${k}_{a,2}$, and ${\beta}_{str}$. In Figure S3, the values of ${k}_{a,1}$ and ${k}_{a,2}$ in all the tests were reported as a function of $\frac{{v}_{e}}{{d}_{50,sand}}{\eta}_{0}$, while ${\beta}_{str}$ was plotted against the effective velocity $v$. A clear linear trend for the two attachment parameters was found, whereas an exponential correlation of ${\beta}_{str}$ with velocity was instead observed. The fitting of the kinetic coefficient trends against Equations (4) and (5) led to the estimation of the following empirical parameters: ${C}_{a,1}=0.13(-)$, ${C}_{a,2}=0.23(-)$, $\omega =0.13$, $\mathsf{\tau}=364.84\mathrm{s}/\mathrm{m}$.

#### 3.3. Radial Injection of mZVI Particles

## 4. Conclusions

## Supplementary Materials

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 2.**Rheological curves of CMC-2000 at 10 g/L, GG at 3 g/L and GG:XG at 1.75 g/L solutions (

**a**), bulk and porous medium rheograms of the XG:GG mixture at 1.75 g/L (

**b**): experimental data (point values) and model (solid line). CMC, carboxymethyl cellulose; GG, guar gum; XG, xanthan gum.

**Figure 3.**(

**a**) frame captured at the end of the test, (

**b**) the total iron concentration map of the radial model, (

**c**) total iron concentration profiles along the three different directions, and (

**d**) the variation of pressure over time measured at 7 cm from the injection well: experimental data (point values) and model (black line).

**Figure 4.**Simulation results for microscale iron (mZVI) particles stabilized through the gel and mZVI particles dispersed in GG only: (

**a**) total iron concentration profiles, (

**b**) the variation of pressure over time measured at 7 cm from the injection well.

Gel Concentration (g/L) | mZVI Conc. (g/L) | Well Radius (m) | $\mathbf{Discharge}\text{}\mathbf{Rate}\text{}({\mathbf{m}}^{3}/\mathbf{h})$ | Injection Duration (min) | Simulation Radius (m) | Cell Number | Inlet Boundary Condition |
---|---|---|---|---|---|---|---|

1.75 | 20 | 0.02 | 1 | 46 | 0.9 | 300 | 3rd Type-Robin |

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**MDPI and ACS Style**

Mondino, F.; Piscitello, A.; Bianco, C.; Gallo, A.; de Folly D’Auris, A.; Tosco, T.; Tagliabue, M.; Sethi, R. Injection of Zerovalent Iron Gels for Aquifer Nanoremediation: Lab Experiments and Modeling. *Water* **2020**, *12*, 826.
https://doi.org/10.3390/w12030826

**AMA Style**

Mondino F, Piscitello A, Bianco C, Gallo A, de Folly D’Auris A, Tosco T, Tagliabue M, Sethi R. Injection of Zerovalent Iron Gels for Aquifer Nanoremediation: Lab Experiments and Modeling. *Water*. 2020; 12(3):826.
https://doi.org/10.3390/w12030826

**Chicago/Turabian Style**

Mondino, Federico, Amelia Piscitello, Carlo Bianco, Andrea Gallo, Alessandra de Folly D’Auris, Tiziana Tosco, Marco Tagliabue, and Rajandrea Sethi. 2020. "Injection of Zerovalent Iron Gels for Aquifer Nanoremediation: Lab Experiments and Modeling" *Water* 12, no. 3: 826.
https://doi.org/10.3390/w12030826