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ARS Home » Pacific West Area » Davis, California » Sustainable Agricultural Water Systems Research » Research » Publications at this Location » Publication #391484

Research Project: A Systems Approach to Improved Water Management for Sustainable Production

Location: Sustainable Agricultural Water Systems Research

Title: Prediction of colloid sticking efficiency at pore-scale and macroscale using a pore network model

item LIN, DANTONG - Tsinghua University
item ZHANG, XINGHAO - Tsinghua University
item HU, LIMING - Tsinghua University
item Bradford, Scott
item SHEN, CHONGYANG - China Agricultural University

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/20/2022
Publication Date: 7/27/2022
Citation: Lin, D., Zhang, X., Hu, L., Bradford, S.A., Shen, C. 2022. Prediction of colloid sticking efficiency at pore-scale and macroscale using a pore network model. Journal of Hydrology. 612(C). Article 128253.

Interpretive Summary: An understanding and ability to predict the transport and fate of colloids in porous media is needed in many agricultural, industrial, and environmental applications, including clogging of soils during managed aquifer recharge and assessing the risks of pathogenic microorganisms. The porous structure of soils is represented using a pore network model, and processes influencing the retention of colloids in soils are systematically studied. Results show a complex dependency on colloid size, solid surface and solution chemistries, and water flow behavior. Colloids that are smaller than around 100 nm are mainly associated with locations with charge or roughness heterogeneities, whereas larger colloids are strongly influenced by water flow and larger roughness features. These results will be of interested to scientists and engineers concerned with managing or mitigating risks of colloids in the environment.

Technical Abstract: The sticking efficiency (a) is a vital parameter to predict the transport and deposition of colloids in porous media. The value of a depends on various factors such as the interaction energy between colloids and the solid-water interface (SWI), kinetic energy fluctuations of diffusing colloids, and the hydrodynamics of the flow field in the pore structure. However, a is usually assumed to be spatially constant and fitted from experimental data. In this study, a theoretical method is proposed to predict the distribution of the sticking efficiency at pore scale (at) using a pore network model (PNM) and the macroscale sticking efficiency of the whole porous media (aM) by means of upscaling. A PNM is established to simulate the pore structure of porous media and to obtain the flow field, and energy and torque balances are calculated throughout the spatial pore structure to determine the distribution of at under different physiochemical conditions. The value of aM is determined through breakthrough curves provided by the PNM under favorable and unfavorable conditions. Results show the distribution of at is sensitive to various factors including colloid characteristics, pore surface features, geochemical environment and hydrodynamic conditions. Colloid characteristics like colloid surface zeta potential, geochemical environment such as solution ionic strength, and pore surface characteristics including nanoscale roughness and especially charge heterogeneity have a controlling influence on at for nanoparticles (<100 nm) due to their impact on interaction energies. Hydrodynamic conditions played an increasingly important and eventually dominant role in determining at for larger colloids by changing the sticking of weakly associated colloids (e.g., at secondary minima). When hydrodynamic torques are weak, the influence of colloid size on at can be non-monotonic due to the combined influence of interaction energy and hydrodynamic torques. As a result, higher values of aM occurred for smaller colloid sizes, lower flow velocities, larger pore sizes, and in the presence of microscopic roughness. The method proposed by this study can be used to predict the sticking efficiency under different solution and solid phase chemistries, nanoscale heterogeneities, microscopic roughness, flow velocities, and pore structure conditions.