Prediction of Nanoparticle Photoreactivity in Mixtures of Surface Foulants Requires Kinetic (Non-equilibrium) Adsorption Considerations.

The adsorption of foulants on photocatalytic nanoparticles can suppress their reactivity in water treatment applications by scavenging reactive species at the photocatalyst surface, screening light, or competing for surface sites. These inhibitory effects are commonly modeled using the Langmuir-Hinshelwood model, assuming that adsorbed layer compositions follow Langmuirian (equilibrium) competitive adsorption. However, this assumption has not been evaluated in complex mixtures of foulants. This study evaluates the photoreactivity of titanium dioxide (TiO2) nanoparticles toward a target compound, phenol, in the presence of two classes of foulants ─ natural organic matter (NOM) and a protein, bovine serum albumin (BSA) ─ and mixtures of the two. Langmuir adsorption models predict that BSA should strongly influence the nanoparticle photoreactivity because of its higher adsorption affinity relative to phenol and NOM. However, model evaluation of the experimental phenol decay rates suggested that neither the phenol nor foulant surface coverages are governed by Langmuirian competitive adsorption. Rather, a reactivity model incorporating kinetic predictions of adsorbed layer compositions (favoring NOM adsorption) outperformed Langmuirian models in providing accurate, unbiased predictions of phenol degradation rates. This research emphasizes the importance of using first-principles models that account for adsorption kinetics when assumptions of equilibrium adsorption do not apply.

Lead phosphate deposition in porous media and implications for lead remediation.

Phosphate addition is commonly applied as an effective method to remediate lead contaminated sites via formation of low solubility lead phosphate solids. However, subsequent transport of the lead phosphate particles may impact the effectiveness of this remediation strategy. Hence, this study investigates the mechanisms involved in the aggregation of lead phosphate particles and their deposition in sand columns as a function of typical water chemistry parameters. Clean bed filtration theory was evaluated to predict the particle deposition behavior, using Derjaguin-Landau-Verwey-Overbeek (DLVO) theory to estimate particle-substrate interactions. The observed particle deposition was not predictable from the primary energy barrier in clean bed filtration models, even in simple monovalent background electrolyte (NaNO3), because weak deposition in a secondary energy minimum prevailed even at low ionic strength, and ripening occurred at ionic strengths of 12.5 mM or higher. For aged (aggregated) suspensions, straining also occurred at 12.5 mM or higher. Aggregation and deposition were further enhanced at low total P/Pb ratios (i.e., P/Pb = 1) and in the presence of divalent cations, such as Ca2+ (≥ 0.2 mM), which resulted in less negative particle surface potentials and weaker electrostatic repulsion forces. However, the presence of 5 mg C/L of humic acid induced strong steric or electrosteric repulsion, which hindered particle aggregation and deposition even in the presence of Ca2+. This study demonstrates the importance of myriad mechanisms in lead phosphate deposition and provides useful information for controlling water chemistry in phosphate applications for lead remediation.

Selective quantification of nanoplastics in environmental matrices by asymmetric flow field-flow fractionation with total organic carbon detection.

Nanoplastics are of rapidly emerging concern as ubiquitous environmental pollutants. However, fate and transport assessments are currently hindered by a need for new analytical methods that can selectively quantify nanoplastics in environmental matrices. This study presents the first proof of principle to hyphenate asymmetric flow field-flow fractionation (AF4) with total organic carbon (TOC) detection for nanoplastics analysis, as evaluated on mixtures of multimodal polystyrene nanoplastics in the presence of dissolved organic matter and clay colloids. The AF4-TOC method enables more robust, size-resolved quantification of nanoplastics over other AF4 detection modes, including UV-vis, refractive index, and fluorescence tagging. This method development can fill a critical gap in analytical methodology for environmental nanoplastics research.