Effects of ultrasound on electrochemical oxidation mechanisms of p-substituted phenols at BDD and PbO2 anodes

The effects of low-frequency (40 kHz) ultrasound are investigated with regard to the effectiveness and mechanisms of electrochemical oxidation of p-substituted phenols (p-nitrophenol, p-hydroxybenzaldehyde, phenol, p-cresol, and p-methoxyphenol) at BDD (boron-doped diamond) and PbO2 anodes. Although ultrasound improved the disappearance rates of p-substituted phenols at both the BDD and PbO2 anodes, the degree of enhancement varied according to the type of p-substituted phenol and type of anode under consideration. At the BDD anode, the % Increase values were in the range 73-83% for p-substituted phenol disappearance and in the range 60-70% for COD removal. However, at the PbO2 anode, the corresponding %Increase values were in the range 50-70% for disappearance of p-substituted phenols and only 5-25% for COD removal, much lower values than obtained at the BDD anode. Further investigations on the influence of ultrasound on the electrochemical oxidation mechanisms at BDD and PbO2 anodes revealed that the different increase extent were due to the specialized electrochemical oxidation mechanisms at these two anodes. The hydroxyl radicals were mainly free at the BDD electrodes with a larger reaction zone, but adsorbed at the PbO2 electrodes with a smaller reaction zone. Therefore, the enhancement due to ultrasound was greater at the BDD anode than at the PbO2 anode. (C) 2010 Elsevier Ltd. All rights reserved.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000280422800007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701ElectrochemistrySCI(E)EI21ARTICLE205569-55755

Remote Sensing Spatiotemporal Assessment of Nitrogen Concentrations in Tampa Bay, Florida due to a Drought

A long-term low nitrogen to phosphorus (N:P) ratio in the Tampa Bay, Florida, estuary system suggests that nitrogen is more limiting than phosphorus. However, south Florida suffered from a drought around 2007, and the reduction in runoff flowing into the bay affected local ecosystem dynamics. This study presents a remote sensing study to retrieve spatiotemporal patterns of total nitrogen (TN) concentrations in Tampa Bay under drought impacts through the integration of Moderate Resolution Imaging Spectroradiometer (MODIS) images and a genetic programming (GP) model. Research findings show that the drought impact on TN in Tampa Bay is both a seasonal and yearly phenomenon. Without the presence of ocean water intrusion, the whole bay would show a relatively uniform TN distribution during the drought period until the flow input from rivers returned to normal. Based on yearly comparisons, temperature could be the limiting factor on the plankton growth in Tampa Bay. To further substantiate the credibility of a nutrient estimation algorithm, a k-means clustering analysis was conducted to demonstrate sea-bay-land interactions among ebbs, tides, and river discharges. The seasonal cluster distribution in 2007 is generally consistent with the conventional segments division of Tampa Bay

(Azido-κN)[6-meth­oxy-2-(2-pyridylmethyl­imino­meth­yl)phenolato-κ3 N,N′,O 1]copper(II)

The title compound, [Cu(C14H13N2O2)(N3)], is a monomeric neutral complex with one unsymmetrical 6-meth­oxy-2-(2-pyridylmethyl­imino­meth­yl)phenolate Schiff base ligand and one azide ligand. The mol­ecules are connected by a combination of two π–π inter­actions [centroid–centroid distances 3.359 (3) and 3.378 (2) Å] and one C—H⋯N hydrogen bond into a two-dimensional supra­molecular network structure

Modelling Fertilizer Use in Relation to Farmers’ Household Characteristics in Three Gorges Reservoir Area, China

Non-point source pollution from excessive use of fertilizers in agriculture is a major cause of the eutrophication problem in China. Understanding farmers’ decision-making concerning fertilization and identifying the influencing factors in this process are key to tackling overfertilization and related pollution issues. This paper reports a study on modelling decisions about fertilizer use based on data collected from 200 farmer households in the Three Gorges Reservoir area of China, using a well-fitted artificial neural network (ANN) with incorporated variance-based sensitivity analysis. The rate of fertilizer use estimated from the model is in good agreement with observed data. The model is further validated and tested by comparing the simulated and observed values. Results show that the model is able to identify the influencing factors and their interactions causing the variation in fertilizer use and to help pinpoint the underlying reasons. It is found that the farmers’ fertilization behavior is greatly affected by the area of cultivated land, followed by the interaction among farmers’ education level, annual income, and awareness of the importance of environmental protection. Future land consolidation is one of several ways to achieve more sustainable fertilization strategies

Modeling of a combined CH₄-assisted solid oxide co-electrolysis and Fischer-Tropsch synthesis system for low-carbon fuel production

10th International Conference on Applied Energy, ICAE 2018, Hong Kong, 22-25 August 2018201906 bcmaVersion of RecordPublishe

Remote Sensing Spatiotemporal Assessment of Nitrogen Concentrations in Tampa Bay, Florida due to a Drought

A long-term low nitrogen to phosphorus (N:P) ratio in the Tampa Bay, Florida, estuary system suggests that nitrogen is more limiting than phosphorus. However, south Florida suffered from a drought around 2007, and the reduction in runoff flowing into the bay affected local ecosystem dynamics. This study presents a remote sensing study to retrieve spatiotemporal patterns of total nitrogen (TN) concentrations in Tampa Bay under drought impacts through the integration of Moderate Resolution Imaging Spectroradiometer (MODIS) images and a genetic programming (GP) model. Research findings show that the drought impact on TN in Tampa Bay is both a seasonal and yearly phenomenon. Without the presence of ocean water intrusion, the whole bay would show a relatively uniform TN distribution during the drought period until the flow input from rivers returned to normal. Based on yearly comparisons, temperature could be the limiting factor on the plankton growth in Tampa Bay. To further substantiate the credibility of a nutrient estimation algorithm, a k-means clustering analysis was conducted to demonstrate sea-bay-land interactions among ebbs, tides, and river discharges. The seasonal cluster distribution in 2007 is generally consistent with the conventional segments division of Tampa Bay

Tetra­aqua­bis(2-methyl­benzimidazolium-1,3-diacetato-κO)zinc(II) tetra­hydrate

The asymmetric unit of the title compound, [Zn(C12H11N2O4)2(H2O)4]·4H2O, contains one-half of the complex mol­ecule and two uncoordin­ated water mol­ecules. The four water O atoms in the equatorial plane around the ZnII centre ( symmetry) form a distorted square-planar arrangement, while the distorted octa­hedral coordination geometry is completed by the O atoms of the zwitterionic 2-methyl­benzimidazolium-1,3-diacetate ligands in the axial positions. The benzimidazole ring system is planar, with a maximum deviation of 0.041 (3) Å. Intra­molecular O—H⋯O hydrogen bonding results in the formation of a non-planar six-membered ring. In the crystal structure, strong intra- and inter­molecular O—H⋯O hydrogen bonds link the mol­ecules into a three-dimensional network. π–π contacts between benzimidazole rings [centroid–centroid distance = 3.899 (1) Å] may further stabilize the structure

Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on–off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis