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Simulating graphene oxide nanomaterial phototransformation and transport in surface water.

ABSTRACT: The production of graphene-family nanomaterials (GFNs) has increased appreciably in recent years. Graphene oxide (GO) has been found to be the most toxic nanomaterial among GFNs and, to our knowledge, no studies have been conducted to model its fate and transport in the environment. Lab studies show that GO undergoes phototransformation in surface waters under sunlight radiation resulting in formation of photoreduced GO (rGO). In this study, the recently updated Water Quality Analysis Simulation Program (WASP8) is used to simulate time-dependent environmental exposure concentrations of GO and its major phototransformation product, rGO, for Brier Creek, GA, USA at two flow scenarios under a constant loading of GO to the river for a period of 20 years. Analysis shows that the degree of phototransformation is closely associated with river flow condition: up to of 40% of GO undergoes phototransformation at low flow condition, whereas only 2.5% of GO phototransformation occurs at mean flow condition. River flow and heteroaggregation exhibit a 'competing' effect in determining the formation of rGO heteroagglomerates. Mass fraction analysis indicates that the vast majority of rGO heteroagglomerates settle to the sediment layers due to the settling of suspended solids. Simulation of natural recovery after removal of the GO source suggests that free GO and rGO are the immediate contaminants of concern in the studied surface water system, while rGO heteroaggregated with suspended solids can have a long-term ecological impact on both the water column and sediments.

SUBMITTER: Han Y

PROVIDER: S-EPMC6621605 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Simulating graphene oxide nanomaterial phototransformation and transport in surface water.

Han Yanlai Y Knightes Christopher D CD Bouchard Dermont D Zepp Richard R Avant Brian B Hsieh Hsin-Se HS Chang Xiaojun X Acrey Brad B Henderson W Matthew WM Spear Jessica J

Environmental science. Nano 20190101 1

The production of graphene-family nanomaterials (GFNs) has increased appreciably in recent years. Graphene oxide (GO) has been found to be the most toxic nanomaterial among GFNs and, to our knowledge, no studies have been conducted to model its fate and transport in the environment. Lab studies show that GO undergoes phototransformation in surface waters under sunlight radiation resulting in formation of photoreduced GO (rGO). In this study, the recently updated Water Quality Analysis Simulation ...[more]

PMID: 31297195

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Project description:Little is known about the fate and transport of the "new-horizon" multifunctional nanohybrids in the environment. Saturated sand-packed column experiments ( n = 66) were therefore performed to investigate the transport and retention of reduced graphene oxide (RGO)-metal oxide (Fe3O4, TiO2, and ZnO) nanohybrids under environmentally relevant conditions (mono- and divalent electrolytes and natural organic matter). Classical colloid science principles (Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and colloid filtration theory (CFT)) and mathematical models based on the one-dimensional convection-dispersion equation were employed to describe and predict the mobility of RGO-Fe3O4, RGO-TiO2, and RGO-ZnO nanohybrids in porous media. Results indicate that the mobility of the three nanohybrids under varying experimental conditions is overall explainable by DLVO theory and CFT. Numerical simulations suggest that the one-site kinetic retention model (OSKRM) considering both time- and depth-dependent retention accurately approximated the breakthrough curves (BTCs) and retention profiles (RPs) of the nanohybrids concurrently; whereas, others (e.g., two-site retention model) failed to capture the BTCs and/or RPs. This is primarily because blocking BTCs and exponential/hyperexponential/uniform RPs occurred, which is within the framework of OSKRM featuring time- (for kinetic Langmuirian blocking) and depth-dependent (for exponential/hyperexponential/uniform) retention kinetics. Employing fitted parameters (maximum solid-phase retention capacity: Smax = 0.0406-3.06 cm3/g; and first-order attachment rate coefficient: ka = 0.133-20.6 min-1) extracted from the OSKRM and environmentally representative physical variables (flow velocity (0.00441-4.41 cm/min), porosity (0.24-0.54), and grain size (210-810 μm)) as initial input conditions, the long-distance transport scenarios (in 500 cm long sand columns) of the three nanohybrids were predicted via forward simulation. Our findings address the existing knowledge gap regarding the impact of physicochemical factors on the transport of the next-generation, multifunctional RGO-metal oxide nanohybrids in the subsurface.

Dataset Information

Simulating graphene oxide nanomaterial phototransformation and transport in surface water.

Publications

Simulating graphene oxide nanomaterial phototransformation and transport in surface water.

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