Efficiency of emulsion flooding for the removal of organic pollutants from soils: A pore-scale study on the effects of oil volume fraction, injection flow rate, and wettability

Emulsion flooding (EF) is a promising in situ strategy for remediating aquifers contaminated with organic pollutants, yet the pore-scale mechanisms driving its efficiency remain unclear. This study investigates EF at the pore scale using calibrated oil-in-water emulsions in micromodels mimicking pollutant infiltration and removal. The analysis systematically examines how emulsion oil volume fraction ϕ , injection flow rate, and micromodel wettability influence pollutant removal and shape the morphology and connectivity of trapped pollutant ganglia, offering a pore-scale insight largely absent from previous EF investigations. Shear-thinning emulsions with sub-pore droplets achieve ∼ 97% recovery at ϕ = 0.72 by combining piston-like displacement with progressive mobilization and fragmentation of residual blobs, a mechanism not observed in low-viscosity Newtonian emulsions ( ϕ ≤ 0.45), which mainly follow water-saturated channels and exhibit poor sweeping efficiency. Wettability strongly influenced recovery by controlling initial pollutant distribution, connectivity, and pore wall coatings; in oil-wet micromodels, highly connected pollutant ganglia restricted the flow of low-concentrated emulsions. During EF, the average size of pollutant-containing pores decreased in water-wet systems, whereas in oil-wet systems, large pollutant islands were eroded with little pore-size selectivity, highlighting the role of pore structure and wettability in optimizing emulsion-based remediation. Residual pollutant blobs aligned mostly perpendicular to flow at maximum recovery, defining a limit for mechanical displacement of the pollutant. Higher injection rates enhanced pollutant mobilization, while excessive emulsion viscosity increased injection pressure, suggesting potential limits for operational feasibility. These findings provide physics-based guidance for optimizing EF operational parameters and underscore its potential for efficient aquifer remediation.