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  • 1.
    Babakhani, Peyman
    et al.
    Univ Leeds, Sch Earth & Environm, Earth Surface Sci Inst, Leeds LS2 9JT, W Yorkshire, England;Univ Liverpool, Sch Engn, Liverpool L69 3GH, Merseyside, England;Natl Tsing Hua Univ, Dept Biomed Engn & Environm Sci, 101,Sect 2,Kuang Fu Rd, Hsinchu 30013, Taiwan.
    Bridge, Jonathan
    Sheffield Hallam Univ, Dept Nat & Built Environm, Howard St, Sheffield S1 1WB, S Yorkshire, England.
    Phenrat, Tanapon
    Naresuan Univ, Fac Engn, Dept Civil Engn, Res Unit Integrated Nat Resources Remediat & Recl, Phitsanulok 65000, Thailand;Naresuan Univ, Fac Engn, Ctr Excellence Sustainabil Hlth Environm & Ind SH, Phitsanulok 65000, Thailand.
    Fagerlund, Fritjof
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
    Doong, Ruey-an
    Univ Liverpool, Sch Engn, Liverpool L69 3GH, Merseyside, England;Natl Chiao Tung Univ, Inst Environm Engn, 1001 Univ Rd, Hsinchu 30010, Taiwan.
    Whittle, Karl R.
    Univ Liverpool, Sch Engn, Liverpool L69 3GH, Merseyside, England.
    Comparison of a new mass-concentration, chain-reaction model with the population-balance model for early- and late-stage aggregation of shattered graphene oxide nanoparticles2019In: Colloids and Surfaces A: Physicochemical and Engineering Aspects, ISSN 0927-7757, E-ISSN 1873-4359, Vol. 582, article id 123862Article in journal (Refereed)
    Abstract [en]

    Aggregation as an essential mechanism impacting nanoparticle (NP) functionality, fate, and transport in the environment is currently modelled using population-balance equation (PBE) models which are computationally expensive when combined with other continuum-scale reactive transport models. We propose a new simple mass-concentration-based, chain-reaction modelling (CRM) framework to alleviate computational expenses of PBE and potentially to facilitate combination with other fate, transport, and reaction models. Model performance is compared with analytical PBE solution and a standard numerical PBE technique (fixed pivot, FP) by fitting against experimental data (i.e., hydrodynamic diameter and derived count rate of dynamic light scattering used as a representative of mass concentration) for early- and late-stage, aggregation of shattered graphene oxide (SGO) NP across a broad range of solution chemistries. In general, the CRM approach demonstrates a better match with the experimental data with a mean Nash-Sutcliffe model efficiency (NSE) coefficient of 0.345 than the FP model with a mean NSE of 0.29. Comparing model parameters (aggregation rate constant and fractal dimension) obtained from fitting CRM and FP to the experimental data, similar trends or ranges are obtained between the two approaches. Computationally, the modified CRM is an order-of-magnitude faster than the FP technique, suggesting that it can be a promising modelling framework for efficient and accurate modelling of NP aggregation. However, in the scope of this study, reaction rate coefficients of the CRM have been linked to collision frequencies based on simplified and empirical relationships which need improvement in future studies.

  • 2.
    Babakhani, Peyman
    et al.
    Islamic Azad University, Tehran Science and Research Branch, Department of Hydrology Engineering, Tehran, Iran.
    Fagerlund, Fritjof
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Colorado School of Mines, Center for Experimental Study of Subsurface Environmental Processes, Golden, CO, USA.
    Shamsai, Abolfazl
    Islamic Azad University, Tehran Science and Research Branch, Department of Hydrology Engineering, Tehran, Iran; Sharif University of Technology, Department of Civil Engineering, Tehran, Iran.
    Lowry, Gregory Victor
    Carnegie Mellon University, Center for Environmental Implications of Nanotechnology (CEINT), Pittsburgh, PA, USA; Carnegie Mellon University, Department of Civil and Environmental Engineering, Pittsburgh, PA, USA.
    Phenrat, Tanapon
    Naresuan University, Faculty of Engineering, Department of Civil Engineering, Research Unit for Integrated Natural Resources Remediation and Reclamation (IN3R), Phitsanulok, Thailand; Naresuan University, Faculty of Engineering, Center of Excellence for Sustainability of Health, Environment and Industry (SHE&I), Phitsanulok, Thailand.
    Modified MODFLOW-based model for simulating the agglomeration and transport of polymer-modified Fe0 nanoparticles in saturated porous media2018In: Environmental science and pollution research international, ISSN 0944-1344, E-ISSN 1614-7499, Vol. 25, no 8, p. 7180-7199Article in journal (Refereed)
    Abstract [en]

    The solute transport model MODFLOW has become a standard tool in risk assessment and remediation design. However, particle transport models that take into account both particle agglomeration and deposition phenomena are far less developed. The main objective of the present study was to evaluate the feasibility of adapting the standard code MODFLOW/MT3D to simulate the agglomeration and transport of three different types of polymer-modified nanoscale zerovalent iron (NZVI) in one-dimensional (1-D) and two-dimensional (2-D) saturated porous media. A first-order decay of the particle population was used to account for the agglomeration of particles. An iterative technique was used to optimize the model parameters. The model provided good matches to 1-D NZVI-breakthrough data sets, with R 2 values ranging from 0.96 to 0.99, and mass recovery differences between the experimental results and simulations ranged from 0.1 to 1.8 %. Similarly, simulations of NZVI transport in the heterogeneous 2-D model demonstrated that the model can be applied to more complicated heterogeneous domains. However, the fits were less good, with the R 2 values in the 2-D modeling cases ranging from 0.75 to 0.95, while the mass recovery differences ranged from 0.7 to 6.5 %. Nevertheless, the predicted NZVI concentration contours during transport were in good agreement with the 2-D experimental observations. The model provides insights into NZVI transport in porous media by mathematically decoupling agglomeration, attachment, and detachment, and it illustrates the importance of each phenomenon in various situations.

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