In-situ electrochemical Fe(VI) for removal of microcystin-LR from drinking water: comparing dosing of the ferrate ion by electrochemical and chemical means.

Harmful algal blooms (HAB) release microtoxins that contaminate drinking water supplies and risk the health of millions annually. Crystalline ferrate(VI) is a powerful oxidant capable of removing algal microtoxins. We investigate in-situ electrochemically produced ferrate from common carbon steel as an on-demand alternative to crystalline ferrate for the removal of microcystin-LR (MC-LR) and compare the removal efficacy for both electrochemical (EC) and chemical dosing methodologies. We report that a very low dose of EC-ferrate in deionized water (0.5 mg FeO42- L-1) oxidizes MC-LR (MC-LR0 = 10 µg L-1) to below the guideline limit (1.0 µg L-1) within 10 minutes' contact time. With bicarbonate or natural organic matter (NOM), doses of 2.0-5.0 mg FeO42- L-1 are required, with lower efficacy of EC-ferrate than crystalline ferrate due to loss of EC-ferrate by water oxidation. To evaluate the EC-ferrate process to concurrently oxidize micropollutants, coagulate NOM, and disinfect drinking water, we spiked NOM-containing real water with MC-LR and Escherichia coli, finding that EC-ferrate is effective at 10.0 mg FeO42- L-1 under normal operation or 2.0 mg FeO42- L-1 if the test water has initial pH optimized. We suggest in-situ EC-ferrate may be appropriate for sporadic HAB events in small water systems as a primary or back-up technology.

Synthesis and characterization of diverse Pt nanostructures in Nafion.

With the aid of TEM characterization, we describe two distinct Pt nanostructures generated via the electroless reduction of Pt(NH3)4(NO2)2 within Nafion. Under one set of conditions, we produce bundles of Pt nanorods that are 2 nm in diameter and 10-20 nm long. These bundled Pt nanorods, uniformly distributed within 5 µm of the Nafion surface, are strikingly similar to the proposed hydrated nanomorphology of Nafion, and therefore strongly suggestive of Nafion templating. By altering the reaction environment (pH, reductant strength, and Nafion hydration), we can also generate nonregular polyhedron Pt nanoparticles that range in size from a few nanometers in diameter up to 20 nm. These Pt nanoparticles form a dense Pt layer within 100-200 nm from the Nafion surface and show a power-law dependence of particle size and distribution on the distance from the Nafion membrane surface. Control over the distribution and the type of Pt nanostructures in the surface region may provide a cost-effective, simple, and scaleable pathway for enhancing manufacturability, activity, stability, and utilization efficiency of Pt catalysts for electrochemical devices.

Mathematically aggregating experts' predictions of possible futures.

Structured protocols offer a transparent and systematic way to elicit and combine/aggregate, probabilistic predictions from multiple experts. These judgements can be aggregated behaviourally or mathematically to derive a final group prediction. Mathematical rules (e.g., weighted linear combinations of judgments) provide an objective approach to aggregation. The quality of this aggregation can be defined in terms of accuracy, calibration and informativeness. These measures can be used to compare different aggregation approaches and help decide on which aggregation produces the "best" final prediction. When experts' performance can be scored on similar questions ahead of time, these scores can be translated into performance-based weights, and a performance-based weighted aggregation can then be used. When this is not possible though, several other aggregation methods, informed by measurable proxies for good performance, can be formulated and compared. Here, we develop a suite of aggregation methods, informed by previous experience and the available literature. We differentially weight our experts' estimates by measures of reasoning, engagement, openness to changing their mind, informativeness, prior knowledge, and extremity, asymmetry or granularity of estimates. Next, we investigate the relative performance of these aggregation methods using three datasets. The main goal of this research is to explore how measures of knowledge and behaviour of individuals can be leveraged to produce a better performing combined group judgment. Although the accuracy, calibration, and informativeness of the majority of methods are very similar, a couple of the aggregation methods consistently distinguish themselves as among the best or worst. Moreover, the majority of methods outperform the usual benchmarks provided by the simple average or the median of estimates.