Parasitic Light Absorption, Rate Laws and Heterojunctions in the Photocatalytic Oxidation of Arsenic(III) Using Composite TiO2 /Fe2 O3.

Composite photocatalyst-adsorbents such as TiO2 /Fe2 O3 are promising materials for the one-step treatment of arsenite contaminated water. However, no previous study has investigated how coupling TiO2 with Fe2 O3 influences the photocatalytic oxidation of arsenic(III). Herein, we develop new hybrid experiment/modelling approaches to study light absorption, charge carrier behaviour and changes in the rate law of the TiO2 /Fe2 O3 system, using UV-Vis spectroscopy, transient absorption spectroscopy (TAS), and kinetic analysis. Whilst coupling TiO2 with Fe2 O3 improves total arsenic removal by adsorption, oxidation rates significantly decrease (up to a factor of 60), primarily due to the parasitic absorption of light by Fe2 O3 (88 % of photons at 368 nm) and secondly due to changes in the rate law from disguised zero-order kinetics to first-order kinetics. Charge transfer across this TiO2 -Fe2 O3 heterojunction is not observed. Our study demonstrates the first application of a multi-adsorbate surface complexation model (SCM) towards describing As(III) oxidation kinetics which, unlike Langmuir-Hinshelwood kinetics, includes the competitive adsorption of As(V). We further highlight the importance of parasitic light absorption and catalyst fouling when designing heterogeneous photocatalysts for As(III) remediation.

Low-cost electrochemical detection of arsenic in the groundwater of Guanajuato state, central Mexico using an open-source potentiostat.

Arsenic is a carcinogenic groundwater contaminant that is toxic even at the parts-per-billion (ppb) level and its on-site determination remains challenging. Colorimetric test strips, though cheap and widely used, often fail to give reliable quantitative data. On the other hand, electrochemical detection is sensitive and accurate but considerably more expensive at the onset. Here, we present a study on arsenic detection in groundwater using a low-cost, open-source potentiostat based on Arduino technology. We tested different types of gold electrodes (screen-printed and microwire) with anodic stripping voltammetry (ASV), achieving low detection limits (0.7 µg L-1). In a study of arsenic contaminated groundwaters in Mexico, the microwire technique provides greater accuracy than test strips (reducing the median error from -50% to +2.9%) and greater precision (reducing uncertainties from ±25% to ±4.9%). Most importantly, the rate of false negatives versus the World Health Organisation's 10 µg L-1 limit was reduced from 50% to 0% (N = 13 samples). Arsenic determination using open-source potentiostats may offer a low-cost option for research groups and NGOs wishing to perform arsenic analysis in-house, yielding superior quantitative data than the more widely used colorimetric test strips.

A Revised Pseudo-Second-Order Kinetic Model for Adsorption, Sensitive to Changes in Adsorbate and Adsorbent Concentrations.

The development of new adsorbent materials for the removal of toxic contaminants from drinking water is crucial toward achieving the United Nations Sustainable Development Goal 6 (clean water and sanitation). The characterization of these materials includes fitting models of adsorption kinetics to experimental data, most commonly the pseudo-second-order (PSO) model. The PSO model, however, is not sensitive to parameters such as adsorbate and adsorbent concentrations (C0 and Cs) and consequently is not able to predict changes in performance as a function of operating conditions. Furthermore, the experimental conditionality of the PSO rate constant, k2, can lead to erroneous conclusions when comparing literature results. In this study, we analyze 103 kinetic experiments from 47 literature sources to develop a relatively simple modification of the PSO rate equation, yielding dqtdt=k'Ct(1-qtqe)2. Unlike the original PSO model, this revised rate equation (rPSO) provides the first-order and zero-order dependencies upon C0 and Cs that we observe empirically. Our new model reduces the residual sum of squares by 66% when using a single rate constant to model multiple adsorption experiments with varying initial conditions. Furthermore, we demonstrate how the rPSO rate constant k' is more appropriate for comparing literature studies, highlighting faster kinetics in the adsorption of arsenic onto alumina versus iron oxides. This revised rate equation should find applications in engineering studies, especially since the rPSO rate constant k' does not show a counter-intuitive inverse relationship with increasing reaction rates when C0 is increased, unlike the PSO rate constant k2.

Improved accuracy in multicomponent surface complexation models using surface-sensitive analytical techniques: Adsorption of arsenic onto a TiO2/Fe2O3 multifunctional sorbent.

Novel composite materials are increasingly developed for water treatment applications with the aim of achieving multifunctional behaviour, e.g. combining adsorption with light-driven remediation. The application of surface complexation models (SCM) is important to understand how adsorption changes as a function of pH, ionic strength and the presence of competitor ions. Component additive (CA) models describe composite sorbents using a combination of single-phase reference materials. However, predictive adsorption modelling using the CA-SCM approach remains unreliable, due to challenges in the quantitative determination of surface composition. In this study, we test the hypothesis that characterisation of the outermost surface using low energy ion scattering (LEIS) improves CA-SCM accuracy. We consider the TiO2/Fe2O3 photocatalyst-sorbents that are increasingly investigated for arsenic remediation. Due to an iron oxide surface coating that was not captured by bulk analysis, LEIS significantly improves the accuracy of our component additive predictions for monolayer surface processes: adsorption of arsenic(V) and surface acidity. We also demonstrate non-component additivity in multilayer arsenic(III) adsorption, due to changes in surface morphology/porosity. Our results demonstrate how surface-sensitive analytical techniques will improve adsorption models for the next generation of composite sorbents.

Portable and rapid arsenic speciation in synthetic and natural waters by an As(V)-selective chemisorbent, validated against anodic stripping voltammetry.

Inorganic arsenic speciation, i.e. the differentiation between arsenite and arsenate, is an important step for any program aiming to address the global issue of arsenic contaminated groundwater, whether for monitoring purposes or the development of new water treatment regimes. Reliable speciation by easy-to-use, portable and cost-effective analytical techniques is still challenging for both synthetic and natural waters. Here we demonstrate the first application of an As(V)-selective chemisorbent material for simple and portable speciation of arsenic using handheld syringes, enabling high sample throughput with minimal set-up costs. We first show that ImpAs efficiently removes As(V) from a variety of synthetic groundwaters with a single treatment, whilst As(III) is not retained. We then exemplify the potential of ImpAs for simple and fast speciation by determining rate constants for the photooxidation of As(III) in the presence of a TiO2 photocatalyst. Finally, we successfully speciate natural waters spiked with a mix of As(III) and As(V) in both Indian and UK groundwaters with less than 5 mg L-1 dissolved iron. Experimental results using ImpAs agreed with anodic stripping voltammetry (ASV), a benchmark portable technique, with analysis conditions optimised here for the groundwaters of South Asia. This new analytical tool is simple, portable and fast, and should find applications within the overall multi-disciplinary remediation effort that is taking place to tackle this worldwide arsenic problem.