451 resultados para Methane emissions modeling
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Graphene has promised many novel applications in nanoscale electronics and sustainable energy due to its novel electronic properties. Computational exploration of electronic functionality and how it varies with architecture and doping presently runs ahead of experimental synthesis yet provides insights into types of structures that may prove profitable for targeted experimental synthesis and characterization. We present here a summary of our understanding on the important aspects of dimension, band gap, defect, and interfacial engineering of graphene based on state-of-the-art ab initio approaches. Some most recent experimental achievements relevant for future theoretical exploration are also covered.
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Methane gas has been identified as the most destructive greenhouse gas (Liu et al., 2004). It was reported that the global warming potential of methane per molecule relative to CO2 is approximately 23 on a 100-year timescale or 62 over a 20-year period (IPCC, 2001). Methane has high C-H bond energy of about 439 kJ/mol and other higher alkanes (or saturated hydrocarbons) also have a very strong C-C and C-H bonds, thus making their molecules to have no empty orbitals of low energy or filled orbitals of high energy that could readily participate in chemical reactions as is the case with unsaturated hydrocarbons such as olefins and alkynes (Crabtree, 1994; Labinger & Bercaw, 2002)...
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An investigation on hydrogen and methane sensing performance of hydrothermally formed niobium tungsten oxide nanorods employed in a Schottky diode structure is presented herein. By implementing tungsten into the surface of the niobium lattice, we create Nb5+ and W5+ oxide states and an abundant number of surface traps, which can collect and hold the adsorbate charge to reinforce a greater bending of the energy bands at the metal/oxide interface. We show experimentally, that extremely large voltage shifts can be achieved by these nanorods under exposure to gas at both room and high temperatures and attribute this to the strong accumulation of the dipolar charges at the interface via the surface traps. Thus, our results demonstrate that niobium tungsten oxide nanorods can be implemented for gas sensing applications, showing ultra-high sensitivities.
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An emerging theme for a nation transiting into a sustainable future is the provision of a low carbon (dioxide) environment. Carbon emission reduction is therefore important for the industry and community as a whole. Buildings contribute immensely to total greenhouse gas emissions, so pragmatic actions need to be taken to cut the amount of carbon emitted by the construction industry. These typically involve strategies such as energy-saving features in the design, construction and operation of building projects. However, a variety of characteristics of the markets and stakeholders involved are suppressing their development. This paper reports on a series of interviews with a variety of Hong Kong construction project participants aimed at identifying the drivers of, and obstacles to, the construction industry's attempts to reduce carbon emissions. The results confirm the main actions currently undertaken are energy efficiency enhancement, green procurement, research and development activities, waste/water management and other technical measures such as the provision of thermal insulation. The majority of the drivers are economical in nature, suggesting that financial aids, and particularly government incentives, are likely to be useful motivators. Also suggested is the increased promotion of the benefits of environmental sustainability to the wider community, in order to alert the general public to the need for reducing the amount of carbon originating from building usage.
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The success of contemporary organizations depends on their ability to make appropriate decisions. Making appropriate decisions is inevitably bound to the availability and provision of relevant information. Information systems should be able to provide information in an efficient way. Thus, within information systems development a detailed analysis of information supply and information demands has to prevail. Based on Syperski’s information set and subset-model we will give an epistemological foundation of information modeling in general and show, why conceptual modeling in particular is capable of specifying effective and efficient information systems. Furthermore, we derive conceptual modeling requirements based on our findings. A short example illustrates the usefulness of a conceptual data modeling technique for the specification of information systems.
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In order to provide realistic data for air pollution inventories and source apportionment at airports, the morphology and composition of ultrafine particles (UFP) in aircraft engine exhaust were measured and characterized. For this purpose, two independent measurement techniques were employed to collect emissions during normal takeoff and landing operations at Brisbane Airport, Australia. PM1 emissions in the airfield were collected on filters and analyzed using the particle-induced X-ray emission (PIXE) technique. Morphological and compositional analyses of individual ultrafine particles in aircraft plumes were performed on silicon nitride membrane grids using transmission electron microscopy (TEM) combined with energy-dispersive X-ray microanalysis (EDX). TEM results showed that the deposited particles were in the range of 5 to 100 nm in diameter, had semisolid spherical shapes and were dominant in the nucleation mode (18 – 20 nm). The EDX analysis showed the main elements in the nucleation particles were C, O, S and Cl. The PIXE analysis of the airfield samples was generally in agreement with the EDX in detecting S, Cl, K, Fe and Si in the particles. The results of this study provide important scientific information on the toxicity of aircraft exhaust and their impact on local air quality.
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Emission rates of ammonia (NH3) are reported for a fleet of 130 light-, medium-, and heavy-duty vehicles recruited in Guangzhou, China. NH3 measurements were performed using Nessler's Reagents spectrophotometry and nationwide standard chassis dynamometer test cycles required by Chinese EPA. Emissions of CO and NOx were also measured during these test cycles. Emission factors of NH3 were calculated for each type of vehicle and used to estimate the total emissions of NH3 from motor vehicles in Guangzhou (GZ) in 2009. Emission factors of NH3 show large variations among different categories of vehicles, with a range from 4 to 138 mg km-1. The average emissions of NH3 in Guangzhou in 2009 were estimated to be 983 t, with a range from 373 to 2136 t. In addition, it was found that vehicles with the highest NH3 emission rates possess the following characteristics: mediumand heavy-duty vehicles, certified with out-of-date emission standards, mid-range odometer readings, and higher CO and NOx emission rates. The results of this study will be useful for developing NH3 emissions inventories in Guangzhou and other urban areas in China.
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In a business environment, making the right decisions is vital for the success of a company. Making right decisions is inevitably bound to the availability and provision of relevant information. Information systems are supposed to be able to provide this information in an efficient way. Thus, within information systems development a detailed analysis of information supply and information demands has to prevail. Based on Szyperski’s information set and subset-model we will give an epistemological foundation of information modeling in general and show, why conceptual modeling in particular is capable of developing effective and efficient information systems. Furthermore, we derive conceptual modeling requirements based on our findings.
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This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.
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Crowds of noncombatants play a large and increasingly recognized role in modern military operations and often create substantial difficulties for the combatant forces involved. However, realistic models of crowds are essentially absent from current military simulations. To address this problem, the authors are developing a crowd simulation capable of generating crowds of noncombatant civilians that exhibit a variety of realistic individual and group behaviors at differing levels of fidelity. The crowd simulation is interoperable with existing military simulations using a standard, distributed simulation architecture. Commercial game technology is used in the crowd simulation to model both urban terrain and the physical behaviors of the human characters that make up the crowd. The objective of this article is to present the design and development process of a simulation that integrates commercially available game technology with current military simulations to generate realistic and believable crowd behavior.
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We report a comprehensive theoretical study on reaction of methane by Fe4 cluster. This Letter gains insight into the mechanism of the reaction and indicate the Fe4 cluster has strong catalytic effect on the activation reaction of methane. In detail, the results show the cleavage of the first C–H bond is both an energetically and kinetically favourable process and the breaking of the second C–H is the rate-determining step. Moreover, our Letter demonstrates that the different cluster size of iron can not only determine the catalytic activity of methane but also control the product selectivity.
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Atmospheric ultrafine particles play an important role in affecting human health, altering climate and degrading visibility. Numerous studies have been conducted to better understand the formation process of these particles, including field measurements, laboratory chamber studies and mathematical modeling approaches. Field studies on new particle formation found that formation processes were significantly affected by atmospheric conditions, such as the availability of particle precursors and meteorological conditions. However, those studies were mainly carried out in rural areas of the northern hemisphere and information on new particle formation in urban areas, especially those in subtropical regions, is limited. In general, subtropical regions display a higher level of solar radiation, along with stronger photochemical reactivity, than those regions investigated in previous studies. However, based on the results of these studies, the mechanisms involved in the new particle formation process remain unclear, particularly in the Southern Hemisphere. Therefore, in order to fill this gap in knowledge, a new particle formation study was conducted in a subtropical urban area in the Southern Hemisphere during 2009, which measured particle size distribution in different locations in Brisbane, Australia. Characterisation of nucleation events was conducted at the campus building of the Queensland University of Technology (QUT), located in an urban area of Brisbane. Overall, the annual average number concentrations of ultrafine, Aitken and nucleation mode particles were found to be 9.3 x 103, 3.7 x 103 and 5.6 x 103 cm-3, respectively. This was comparable to levels measured in urban areas of northern Europe, but lower than those from polluted urban areas such as the Yangtze River Delta, China and Huelva and Santa Cruz de Tenerife, Spain. Average particle number concentration (PNC) in the Brisbane region did not show significant seasonal variation, however a relatively large variation was observed during the warmer season. Diurnal variation of Aitken and nucleation mode particles displayed different patterns, which suggested that direct vehicle exhaust emissions were a major contributor of Aitken mode particles, while nucleation mode particles originated from vehicle exhaust emissions in the morning and photochemical production at around noon. A total of 65 nucleation events were observed during 2009, in which 40 events were classified as nucleation growth events and the remainder were nucleation burst events. An interesting observation in this study was that all nucleation growth events were associated with vehicle exhaust emission plumes, while the nucleation burst events were associated with industrial emission plumes from an industrial area. The average particle growth rate for nucleation events was found to be 4.6 nm hr-1 (ranging from 1.79-7.78 nm hr-1), which is comparable to other urban studies conducted in the United States, while monthly particle growth rates were found to be positively related to monthly solar radiation (r = 0.76, p <0.05). The particle growth rate values reported in this work are the first of their kind to be reported for the subtropical urban area of Australia. Furthermore, the influence of nucleation events on PNC within the urban airshed was also investigated. PNC was simultaneously measured at urban (QUT), roadside (Woolloongabba) and semi-urban (Rocklea) sites in Brisbane during 2009. Total PNC at these sites was found to be significantly affected by regional nucleation events. The relative fractions of PNC to total daily PNC observed at QUT, Woolloongabba and Rocklea were found to be 12%, 9% and 14%, respectively, during regional nucleation events. These values were higher than those observed as a result of vehicle exhaust emissions during weekday mornings, which ranged from 5.1-5.5% at QUT and Woolloongabba. In addition, PNC in the semi-urban area of Rocklea increased by a factor of 15.4 when it was upwind from urban pollution sources under the influence of nucleation burst events. Finally, we investigated the influence of sulfuric acid on new particle formation in the study region. A H2SO4 proxy was calculated by using [SO2], solar radiation and particle condensation sink data to represent the new particle production strength for the urban, roadside and semi-urban areas of Brisbane during the period June-July of 2009. The temporal variations of the H2SO4 proxies and the nucleation mode particle concentration were found to be in phase during nucleation events in the urban and roadside areas. In contrast, the peak of proxy concentration occurred 1-2 hr prior to the observed peak in nucleation mode particle concentration at the downwind semi-urban area of Brisbane. A moderate to strong linear relationship was found between the proxy and the freshly formed particles, with r2 values of 0.26-0.77 during the nucleation events. In addition, the log[H2SO4 proxy] required to produce new particles was found to be ~1.0 ppb Wm-2 s and below 0.5 ppb Wm-2 s for the urban and semi-urban areas, respectively. The particle growth rates were similar during nucleation events at the three study locations, with an average value of 2.7 ± 0.5 nm hr-1. This result suggested that a similar nucleation mechanism dominated in the study region, which was strongly related to sulphuric acid concentration, however the relationship between the proxy and PNC was poor in the semi-urban area of Rocklea. This can be explained by the fact that the nucleation process was initiated upwind of the site and the resultant particles were transported via the wind to Rocklea. This explanation is also supported by the higher geometric mean diameter value observed for particles during the nucleation event and the time lag relationship between the H2SO4 proxy and PNC observed at Rocklea. In summary, particle size distribution was continuously measured in a subtropical urban area of southern hemisphere during 2009, the findings from which formed the first particle size distribution dataset in the study region. The characteristics of nucleation events in the Brisbane region were quantified and the properties of the nucleation growth and burst events are discussed in detail using a case studies approach. To further investigate the influence of nucleation events on PNC in the study region, PNC was simultaneously measured at three locations to examine the spatial variation of PNC during the regional nucleation events. In addition, the impact of upwind urban pollution on the downwind semi-urban area was quantified during these nucleation events. Sulphuric acid was found to be an important factor influencing new particle formation in the urban and roadside areas of the study region, however, a direct relationship with nucleation events at the semi-urban site was not observed. This study provided an overview of new particle formation in the Brisbane region, and its influence on PNC in the surrounding area. The findings of this work are the first of their kind for an urban area in the southern hemisphere.
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Recent advances in computational geodynamics are applied to explore the link between Earth’s heat, its chemistry and its mechanical behavior. Computational thermal-mechanical solutions are now allowing us to understand Earth patterns by solving the basic physics of heat transfer. This approach is currently used to solve basic convection patterns of terrestrial planets. Applying the same methodology to smaller scales delivers promising similarities between observed and predicted structures which are often the site of mineral deposits. The new approach involves a fully coupled solution to the energy, momentum and continuity equations of the system at all scales, allowing the prediction of fractures, shear zones and other typical geological patterns out of a randomly perturbed initial state. The results of this approach are linking a global geodynamic mechanical framework over regional-scale mineral deposits down to the underlying micro-scale processes. Ongoing work includes the challenge of incorporating chemistry into the formulation.
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We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.
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Density functional theory (DFT) calculations have been carried out to explore the catalytic activation of C–H bonds in methane by the iron atom, Fe, and the iron dimer, Fe2. For methane activation on an Fe atom, the calculations suggest that the activation of the first C–H bond is mediated via the triplet excited-state potential energy surface (PES), with initial excitation of Fe to the triplet state being necessary for the reaction to be energetically feasible. Compared with the breaking of the first C–H bond, the cleavage of the second C–H bond is predicted to involve a significantly higher barrier, which could explain experimental observations of the HFeCH3 complex rather than CH2FeH2 in the activation of methane by an Fe atom. For methane activation on an iron dimer, the cleavage of the first C–H bond is quite facile with a barrier only 11.2, 15.8 and 8.4 kcal/mol on the septet state energy surface at the B3LYP/6-311+G(2df,2dp), BPW91/6-311+G(2df,2dp) and M06/B3LYP level, respectively. Cleavage of the second C–H bond from HFe2CH3 involves a barrier calculated respectively as 18.0, 10.7 and 12.4 kcal/mol at the three levels. The results suggest that the elimination of hydrogen from the dihydrogen complex is a rate-determining step. Overall, our results indicate that the iron dimer Fe2 has a stronger catalytic effect on the activation of methane than the iron atom.