Transformation of pristine and citrate-functionalized CeO2 nanoparticles in a laboratory-scale activated sludge reactor.

Engineered nanomaterials (ENMs) are used to enhance the properties of many manufactured products and technologies. Increased use of ENMs will inevitably lead to their release into the environment. An important route of exposure is through the waste stream, where ENMs will enter wastewater treatment plants (WWTPs), undergo transformations, and be discharged with treated effluent or biosolids. To better understand the fate of a common ENM in WWTPs, experiments with laboratory-scale activated sludge reactors and pristine and citrate-functionalized CeO2 nanoparticles (NPs) were conducted. Greater than 90% of the CeO2 introduced was observed to associate with biosolids. This association was accompanied by reduction of the Ce(IV) NPs to Ce(III). After 5 weeks in the reactor, 44 ± 4% reduction was observed for the pristine NPs and 31 ± 3% for the citrate-functionalized NPs, illustrating surface functionality dependence. Thermodynamic arguments suggest that the likely Ce(III) phase generated would be Ce2S3. This study indicates that the majority of CeO2 NPs (>90% by mass) entering WWTPs will be associated with the solid phase, and a significant portion will be present as Ce(III). At maximum, 10% of the CeO2 will remain in the effluent and be discharged as a Ce(IV) phase, governed by cerianite (CeO2).

Size-dependent Pb sorption to nanohematite in the presence and absence of a microbial siderophore.

This study focused on the effects of particle size (40, 8.6, and 3.6 nm) and the presence of the microbial ligand desferrioxamine B (DFOB) on Pb(II) sorption to hematite, based on sorption edge experiments (i.e., sorption as a function of pH). Effects of hematite nanoparticle size on sorption edges, when plotted either as sorption density or as % Pb uptake, depended on whether the experiments were normalized to account for differences in specific surface area within the reaction vessels or postnormalized after the fact. Accounting for specific surface area within reaction vessels is needed to maintain comparable ratios of sorbate to sorbent surface sites. When normalized for BET specific surface area (A(s,BET)) within the reaction vessels, the Pb(II) sorption edge shifted ∼0.5 pH units to the left for <10 nm hematite particles, but maximum sorption density (at pH ≥ 6) was unaffected by particle size. DFOB had little or no effect on Pb(II) sorption to <10 nm particles, but DFOB decreased Pb(II) sorption to the 40 nm particles at pH ≥ 6 by ∼20%. Hematite (nano)particle size thus exerts subtle effects on Pb(II) sorption, but the effects may be more pronounced in the presence of a metal complexing agent.

Monte Carlo simulations of the transformation and removal of Ag, TiO2, and ZnO nanoparticles in wastewater treatment and land application of biosolids.

The use of nano-enabled materials in industry and consumer products is increasing rapidly and with it, the more imperative it becomes to understand the consequences of such materials entering the environment during production, use or disposal. The novel properties of engineered nanomaterials (ENMs) that make them desirable for commercial applications also present the possibility of impacting aquatic and terrestrial environments in ways that may differ from materials in bulk format. Modeling techniques are needed to proactively predict the environmental fate and transport of nanomaterials. A model for nanoparticle (NP) separation and transformation in water treatment was parameterized for three metal and metal-oxide NPs. Functional assays to determine NP specific distribution and transformation were used to parameterize the model and obtain environmentally relevant concentrations of NPs and transformation byproducts leaving WWTPs in effluent and biosolids. All three NPs were predicted to associate >90% with the solid phase indicating significant accumulation in the biosolids. High rates of transformation for ZnO and Ag NPs resulted in ~97% transformation of the NPs that enter the plant despite differences in transformation rate in aerobic versus anaerobic environments. Due to high insolubility and negligible redox transformation, the only process predicted to impact TiO2 NP fate and transport in WWTPs was distribution between the solid and liquid phases. Subsequent investigation of ZnO NP species fate and transport when land applied in biosolids indicated that steady state concentrations of ZnO phases would likely be achieved after approximately 150days under loading conditions of biosolids typical in current practice.

Heteroaggregation, transformation and fate of CeO2 nanoparticles in wastewater treatment.

Wastewater Treatment Plants (WWTPs) are a key pathway by which nanoparticles (NPs) enter the environment following release from NP-enabled products. This work considers the fate and exposure of CeO2 NPs in WWTPs in a two-step process of heteroaggregation with bacteria followed by the subsequent reduction of Ce(IV) to Ce(III). Measurements of NP association with solids in sludge were combined with experimental estimates of reduction rate constants for CeO2 NPs in Monte Carlo simulations to predict the concentrations and speciation of Ce in WWTP effluents and biosolids. Experiments indicated preferential accumulation of CeO2 NPs in biosolids where reductive transformation would occur. Surface functionalization was observed to impact both the distribution coefficient and the rates of transformation. The relative affinity of CeO2 NPs for bacterial suspensions in sludge appears to explain differences in the observed rates of Ce reduction for the two types of CeO2 NPs studied.

Validation and sensitivity of the FINE Bayesian network for forecasting aquatic exposure to nano-silver.

The adaptive nature of the Forecasting the Impacts of Nanomaterials in the Environment (FINE) Bayesian network is explored. We create an updated FINE model (FINEAgNP-2) for predicting aquatic exposure concentrations of silver nanoparticles (AgNP) by combining the expert-based parameters from the baseline model established in previous work with literature data related to particle behavior, exposure, and nano-ecotoxicology via parameter learning. We validate the AgNP forecast from the updated model using mesocosm-scale field data and determine the sensitivity of several key variables to changes in environmental conditions, particle characteristics, and particle fate. Results show that the prediction accuracy of the FINEAgNP-2 model increased approximately 70% over the baseline model, with an error rate of only 20%, suggesting that FINE is a reliable tool to predict aquatic concentrations of nano-silver. Sensitivity analysis suggests that fractal dimension, particle diameter, conductivity, time, and particle fate have the most influence on aquatic exposure given the current knowledge; however, numerous knowledge gaps can be identified to suggest further research efforts that will reduce the uncertainty in subsequent exposure and risk forecasts.