267 resultados para nitrogen oxide reduction

em Queensland University of Technology - ePrints Archive


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The effects of electron irradiation on NiO-containing solid solution systems are described. Partially hydrated NiO solid solutions, e. g. , NiO-MgO, undergo surface reduction to Ni metal after examination by TEM. This surface layer results in the formation of Moire interference patterns.

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Graphene, functionalized with oleylamine (OA) and soluble in non-polar organic solvents, was produced on a large scale with a high yield by combining the Hummers process for graphite oxidation, an amine-coupling process to make OA-functionalized graphite oxide (OA-GO), and a novel reduction process using trioctylphosphine (TOP). TOP acts as both a reducing agent and an aggregation-prevention surfactant in the reduction of OA-GO in 1,2-dichlorobenzene (DCB). The reduction of OA-GO is confirmed by X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, and Raman spectroscopy. The exfoliation of GO, OA GO, and OA-functionalized graphene (OA-G) is verified by atomic force microscopy. The conductivity of TOP-reduced OA G, which is deduced from the current–voltage characteristics of a vacuum-filtered thin film, shows that the reduction of functionalized GO by TOP is as effective as the reduction of GO by hydrazine.

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Background: Inflammation and biomechanical factors have been associated with the development of vulnerable atherosclerotic plaques. Lipid-lowering therapy has been shown to be effective in stabilizing them by reducing plaque inflammation. Its effect on arterial wall strain, however, remains unknown. The aim of the present study was to investigate the role of high- and low-dose lipid-lowering therapy using an HMG-CoA reductase inhibitor, atorvastatin, on arterial wall strain. Methods and Results: Forty patients with carotid stenosis >40% were successfully followed up during the Atorvastatin Therapy: Effects on Reduction Of Macrophage Activity (ATHEROMA; ISRCTN64894118) Trial. All patients had plaque inflammation as shown by intraplaque accumulation of ultrasmall super paramagnetic particles of iron oxide on magnetic resonance imaging at baseline. Structural analysis was performed and change of strain was compared between high- and low-dose statin at 0 and 12 weeks. There was no significant difference in strain between the 2 groups at baseline (P=0.6). At 12 weeks, the maximum strain was significantly lower in the 80-mg group than in the 10-mg group (0.085±0.033 vs. 0.169±0.084; P=0.001). A significant reduction (26%) of maximum strain was observed in the 80-mg group at 12 weeks (0.018±0.02; P=0.01). Conclusions: Aggressive lipid-lowering therapy is associated with a significant reduction in arterial wall strain. The reduction in biomechanical strain may be associated with reductions in plaque inflammatory burden.

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Metastable, active, or nonequilibrium states due to the presence of abnormal structures and various types of defects are well known in metallurgy. The role of such states at gold surfaces in neutral aqueous media (an important electrode system in the microsensor area) was explored using cyclic voltammetry. It was demonstrated that, as postulated in earlier work from this laboratory, there is a close relationship between premonolayer oxidation, multilayer hydrous oxide reduction and electrocatalytic behaviour in the case of this and other metal electrode systems. Some of the most active, and therefore most important, entities at surfaces (e.g., metal adatoms) are not readily imageable or detectable by high resolution surface microscopy techniques. Cyclic voltammetry, however, provides significant, though not highly specific, information about such species. The main conclusion is that further practical and theoretical work on active states of metal surfaces is highly desirable as their behaviour is not simple and is of major importance in many electrocatalytic processes.

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Non-thermal plasma (NTP) has been introduced over the past several years as a promising method for nitrogen oxide (NOx) removal. The intent, when using NTP, is to selectively transfer input electrical energy to the electrons, and to not expend this in heating the entire gas stream, which generates free radicals through collisions, and promotes the desired chemical changes in the exhaust gases. The generated active species react with the pollutant molecules and decompose them. This paper reviews and summarizes relevant literature regarding various aspects of the application of {NTP} technology on {NOx} removal from exhaust gases. A comprehensive description of available scientific literature on {NOx} removal using {NTP} technology is presented, including various types of NTP, e.g. dielectric barrier discharge, corona discharge and electron beam. Furthermore, the combination of {NTP} with catalyst and adsorbent for better {NOx} removal efficiency is presented in detail. The removal of {NOx} from both simulated gases and real diesel engines is also considered in this review paper. As {NTP} is a new technique and is not yet commercialized, there is a need for more studies to be performed in this field.

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We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

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There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

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Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.

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Nitrous oxide (N2O) is a major greenhouse gas (GHG) product of intensive agriculture. Fertilizer nitrogen (N) rate is the best single predictor of N2O emissions in row-crop agriculture in the US Midwest. We use this relationship to propose a transparent, scientifically robust protocol that can be utilized by developers of agricultural offset projects for generating fungible GHG emission reduction credits for the emerging US carbon cap and trade market. By coupling predicted N2O flux with the recently developed maximum return to N (MRTN) approach for determining economically profitable N input rates for optimized crop yield, we provide the basis for incentivizing N2O reductions without affecting yields. The protocol, if widely adopted, could reduce N2O from fertilized row-crop agriculture by more than 50%. Although other management and environmental factors can influence N2O emissions, fertilizer N rate can be viewed as a single unambiguous proxy—a transparent, tangible, and readily manageable commodity. Our protocol addresses baseline establishment, additionality, permanence, variability, and leakage, and provides for producers and other stakeholders the economic and environmental incentives necessary for adoption of agricultural N2O reduction offset projects.

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Carbon sequestration in agricultural, forest, and grassland soils has been promoted as a means by which substantial amounts of CO2 may be removed from the atmosphere, but few studies have evaluated the associated impacts on changes in soil N or net global warming potential (GWP). The purpose of this research was to ( 1) review the literature to examine how changes in grassland management that affect soil C also impact soil N, ( 2) assess the impact of different types of grassland management on changes in soil N and rates of change, and (3) evaluate changes in N2O fluxes from differently managed grassland ecosystems to assess net impacts on GWP. Soil C and N stocks either both increased or both decreased for most studies. Soil C and N sequestration were tightly linked, resulting in little change in C: N ratios with changes in management. Within grazing treatments N2O made a minor contribution to GWP (0.1-4%), but increases in N2O fluxes offset significant portions of C sequestration gains due to fertilization (10-125%) and conversion (average = 27%). Results from this work demonstrate that even when improved management practices result in considerable rates of C and N sequestration, changes in N2O fluxes can offset a substantial portion of gains by C sequestration. Even for cases in which C sequestration rates are not entirely offset by increases in N2O fluxes, small increases in N2O fluxes can substantially reduce C sequestration benefits. Conversely, reduction of N2O fluxes in grassland soils brought about by changes in management represents an opportunity to reduce the contribution of grasslands to net greenhouse gas forcing.

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The possibility of a surface inner sphere electron transfer mechanism leading to the coating of gold via the surface reduction of gold(I) chloride on metal and semi-metal oxide nanoparticles was investigated. Silica and zinc oxide nanoparticles are known to have very different surface chemistry, potentially leading to a new class of gold coated nanoparticles. Monodisperse silica nanoparticles were synthesised by the well known Stöber protocol in conjunction with sonication. The nanoparticle size was regulated solely by varying the amount of ammonia solution added. The presence of surface hydroxyl groups was investigated by liquid proton NMR. The resultant nanoparticle size was directly measured by the use of TEM. The synthesised silica nanoparticles were dispersed in acetonitrile (MeCN) and added to a bis acetonitrile gold(I) co-ordination complex [Au(MeCN)2]+ in MeCN. The silica hydroxyl groups were deprotonated in the presence of MeCN generating a formal negative charge on the siloxy groups. This allowed the [Au(MeCN)2]+ complex to undergo ligand exchange with the silica nanoparticles, which formed a surface co-ordination complex with reduction to gold(0), that proceeded by a surface inner sphere electron transfer mechanism. The residual [Au(MeCN)2]+ complex was allowed to react with water, disproportionating into gold(0) and gold(III) respectively, with gold(0) being added to the reduced gold already bound on the silica surface. The so-formed metallic gold seed surface was found to be suitable for the conventional reduction of gold(III) to gold(0) by ascorbic acid. This process generated a thin and uniform gold coating on the silica nanoparticles. This process was modified to include uniformly gold coated composite zinc oxide nanoparticles (Au@ZnO NPs) using surface co-ordination chemistry. AuCl dissolved in acetonitrile (MeCN) supplied chloride ions which were adsorbed onto ZnO NPs. The co-ordinated gold(I) was reduced on the ZnO surface to gold(0) by the inner sphere electron transfer mechanism. Addition of water disproportionated the remaining gold(I) to gold(0) and gold(III). Gold(0) bonded to gold(0) on the NP surface with gold(III) was reduced to gold(0) by ascorbic acid (ASC), which completed the gold coating process. This gold coating process of Au@ZnO NPs was modified to incorporate iodide instead of chloride. ZnO NPs were synthesised by the use of sodium oxide, zinc iodide and potassium iodide in refluxing basic ethanol with iodide controlling the presence of chemisorbed oxygen. These ZnO NPs were treated by the addition of gold(I) chloride dissolved in acetonitrile leaving chloride anions co-ordinated on the ZnO NP surface. This allowed acetonitrile ligands in the added [Au(MeCN)2]+ complex to surface exchange with adsorbed chloride from the dissolved AuCl on the ZnO NP surface. Gold(I) was then reduced by the surface inner sphere electron transfer mechanism. The presence of the reduced gold on the ZnO NPs allowed adsorption of iodide to generate a uniform deposition of gold onto the ZnO NP surface without the use of additional reducing agents or heat.

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The structure of Cu-ZSM-5 catalysts that show activity for direct NO decomposition and selective catalytic reduction of NOx by hydrocarbons has been investigated by a multitude of modern surface analysis and spectroscopy techniques including X-ray photoelectron spectroscopy, thermogravimetric analysis, and in situ Fourier transform infrared spectroscopy. A series of four catalysts were prepared by exchange of Na-ZSM-5 with dilute copper acetate, and the copper loading was controlled by variation of the solution pH. Underexchanged catalysts contained isolated Cu2+OH-(H2O) species and as the copper loading was increased Cu2+ ions incorporated into the zeolite lattice appeared. The sites at which the latter two copper species were located were fundamentally different. The Cu2+OH-(H2O) moieties were bound to two lattice oxygen ions and associated with one aluminum framework species. In contrast, the Cu2+ ions were probably bound to four lattice oxygen ions and associated with two framework aluminum ions. Once the Cu-ZSM-5 samples attained high levels of exchange, the development of [Cu(μ-OH)2Cu]n2+OH-(H2O) species along with a small concentration of Cu(OH)2 was observed. On activation in helium to 500°C the Cu2+OH-(H2O) species transformed into Cu2+O- and Cu+ moieties, whereas the Cu2+ ions were apparently unaffected by this treatment (apart from the loss of ligated water molecules). Calcination of the precursors resulted in the formation of Cu2+O2- and a one-dimensional CuO species. Temperature-programmed desorption studies revealed that oxygen was removed from the latter two species at 407 and 575°C, respectively. © 1999 Academic Press.

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Global cereal production will need to increase by 50% to 70% to feed a world population of about 9 billion by 2050. This intensification is forecast to occur mostly in subtropical regions, where warm and humid conditions can promote high N2O losses from cropped soils. To secure high crop production without exacerbating N2O emissions, new nitrogen (N) fertiliser management strategies are necessary. This one-year study evaluated the efficacy of a nitrification inhibitor (3,4-dimethylpyrazole phosphate—DMPP) and different N fertiliser rates to reduce N2O emissions in a wheat–maize rotation in subtropical Australia. Annual N2O emissions were monitored using a fully automated greenhouse gas measuring system. Four treatments were fertilized with different rates of urea, including a control (40 kg-N ha−1 year−1), a conventional N fertiliser rate adjusted on estimated residual soil N (120 kg-N ha−1 year−1), a conventional N fertiliser rate (240 kg-N ha−1 year−1) and a conventional N fertiliser rate (240 kg-N ha−1 year−1) with nitrification inhibitor (DMPP) applied at top dressing. The maize season was by far the main contributor to annual N2O emissions due to the high soil moisture and temperature conditions, as well as the elevated N rates applied. Annual N2O emissions in the four treatments amounted to 0.49, 0.84, 2.02 and 0.74 kg N2O–N ha−1 year−1, respectively, and corresponded to emission factors of 0.29%, 0.39%, 0.69% and 0.16% of total N applied. Halving the annual conventional N fertiliser rate in the adjusted N treatment led to N2O emissions comparable to the DMPP treatment but extensively penalised maize yield. The application of DMPP produced a significant reduction in N2O emissions only in the maize season. The use of DMPP with urea at the conventional N rate reduced annual N2O emissions by more than 60% but did not affect crop yields. The results of this study indicate that: (i) future strategies aimed at securing subtropical cereal production without increasing N2O emissions should focus on the fertilisation of the summer crop; (ii) adjusting conventional N fertiliser rates on estimated residual soil N is an effective practice to reduce N2O emissions but can lead to substantial yield losses if the residual soil N is not assessed correctly; (iii) the application of DMPP is a feasible strategy to reduce annual N2O emissions from sub-tropical wheat–maize rotations. However, at the N rates tested in this study DMPP urea did not increase crop yields, making it impossible to recoup extra costs associated with this fertiliser. The findings of this study will support farmers and policy makers to define effective fertilisation strategies to reduce N2O emissions from subtropical cereal cropping systems while maintaining high crop productivity. More research is needed to assess the use of DMPP urea in terms of reducing conventional N fertiliser rates and subsequently enable a decrease of fertilisation costs and a further abatement of fertiliser-induced N2O emissions.

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Sub-oxide-to-metallic highly-crystalline nanowires with uniformly distributed nanopores in the 3 nm range have been synthesized by a unique combination of the plasma oxidation, re-deposition and electron-beam reduction. Electron beam exposure-controlled oxide → sub-oxide → metal transition is explained using a non-equilibrium model.