982 resultados para Aircraft exhaust emissions.
Resumo:
Microbial activity in soils is the main source of nitrous oxide (N2O) to the atmosphere. Nitrous oxide is a strong greenhouse gas in the troposphere and participates in ozone destructive reactions in the stratosphere. The constant increase in the atmospheric concentration, as well as uncertainties in the known sources and sinks of N2O underline the need to better understand the processes and pathways of N2O in terrestrial ecosystems. This study aimed at quantifying N2O emissions from soils in northern Europe and at investigating the processes and pathways of N2O from agricultural and forest ecosystems. Emissions were measured in forest ecosystems, agricultural soils and a landfill, using the soil gradient, chamber and eddy covariance methods. Processes responsible for N2O production, and the pathways of N2O from the soil to the atmosphere, were studied in the laboratory and in the field. These ecosystems were chosen for their potential importance to the national and global budget of N2O. Laboratory experiments with boreal agricultural soils revealed that N2O production increases drastically with soil moisture content, and that the contribution of the nitrification and denitrification processes to N2O emissions depends on soil type. Laboratory study with beech (Fagus sylvatica) seedlings demonstrated that trees can serve as conduits for N2O from the soil to the atmosphere. If this mechanism is important in forest ecosystems, the current emission estimates from forest soils may underestimate the total N2O emissions from forest ecosystems. Further field and laboratory studies are needed to evaluate the importance of this mechanism in forest ecosystems. The emissions of N2O from northern forest ecosystems and a municipal landfill were highly variable in time and space. The emissions of N2O from boreal upland forest soil were among the smallest reported in the world. Despite the low emission rates, the soil gradient method revealed a clear seasonal variation in N2O production. The organic topsoil was responsible for most of the N2O production and consumption in this forest soil. Emissions from the municipal landfill were one to two orders of magnitude higher than those from agricultural soils, which are the most important source of N2O to the atmosphere. Due to their small areal coverage, landfills only contribute minimally to national N2O emissions in Finland. The eddy covariance technique was demonstrated to be useful for measuring ecosystem-scale emissions of N2O in forest and landfill ecosystems. Overall, more measurements and integration between different measurement techniques are needed to capture the large variability in N2O emissions from natural and managed northern ecosystems.
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A decentralized emission inventories are prepared for road transport sector of India in order to design and implement suitable technologies and policies for appropriate mitigation measures. Globalization and liberalization policies of the government in 90's have increased the number of road vehicles nearly 92.6% from 1980-1981 to 2003-2004. These vehicles mainly consume non-renewable fossil fuels, and are a major contributor of green house gases, particularly CO2 emission. This paper focuses on the statewise road transport emissions (CO2, CH4, CO, N-x, N2O, SO2, PM and HC) using region specific mass emission factors for each type of vehicles. The country level emissions (CO2, CH4, CO, NOx, N2O, SO2 and NMVOC) are calculated for railways, shipping and airway, based on fuel types. In India, transport sector emits an estimated 258.10 Tg Of CO2, of which 94.5% was contributed by road transport (2003-2004). Among all the states and Union Territories, Maharashtra's contribution is the largest, 28.85 Tg (11.8%) Of CO2, followed by Tamil Nadu 26.41 Tg(10.8%), Gujarat 23.31 Tg(9.6%), Uttar Pradesh 17.42 Tg(7.1%), Rajasthan 15.17 Tg (6.22%) and, Karnataka 15.09 Tg (6.19%). These six states account for 51.8% of the CO2 emissions from road transport.
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This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.
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This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.
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The application of computer-aided inspection integrated with the coordinate measuring machine and laser scanners to inspect manufactured aircraft parts using robust registration of two-point datasets is a subject of active research in computational metrology. This paper presents a novel approach to automated inspection by matching shapes based on the modified iterative closest point (ICP) method to define a criterion for the acceptance or rejection of a part. This procedure improves upon existing methods by doing away with the following, viz., the need for constructing either a tessellated or smooth representation of the inspected part and requirements for an a priori knowledge of approximate registration and correspondence between the points representing the computer-aided design datasets and the part to be inspected. In addition, this procedure establishes a better measure for error between the two matched datasets. The use of localized region-based triangulation is proposed for tracking the error. The approach described improves the convergence of the ICP technique with a dramatic decrease in computational effort. Experimental results obtained by implementing this proposed approach using both synthetic and practical data show that the present method is efficient and robust. This method thereby validates the algorithm, and the examples demonstrate its potential to be used in engineering applications.
Resumo:
Reticulated porous Ti3AlC2 ceramic, a member of the MAX-phase family (Mn+1AXn phases, where M is an early transition metal, A is an A-group element, and X is carbon and/or nitrogen), was prepared from the highly dispersed aqueous suspension by a replica template method. Through a cathodic electrogeneration method, nanocrystalline catalytic CeO2 coatings were deposited on the conductive porous Ti 3AlC2 supports. By adjusting the pH value and cathodic deposition current, coatings exhibiting nanocellar, nanosheets-like, or bubble-free morphologies can be obtained. This work expects to introduce a novel practically feasible material system and a catalytic coating preparation technique for gas exhaust catalyst devices.
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Emissions of gases and particles from sea-faring ships have been shown to impact on the atmospheric chemistry and climate. To efficiently monitor and report these emissions found from a ship’s plume, the concept of using a multi-rotor or UAV to hover inside or near the exhaust of the ship to actively record the data in real time is being developed. However, for the required sensors obtain the data; their sensors must face into the airflow of the ships plume. This report presents an approach to have sensors able to read in the chemicals and particles emitted from the ship without affecting the flight dynamics of the multi-rotor UAV by building a sealed chamber in which a pump can take in the surrounding air (outside the downwash effect of the multi-rotor) where the sensors are placed and can analyse the gases safely. Results show that the system is small, lightweight and air-sealed and ready for flight test.
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The goal of this study is the multi-mode structural vibration control in the composite fin-tip of an aircraft. Structural model of the composite fin-tip with surface bonded piezoelectric actuators is developed using the finite element method. The finite element model is updated experimentally to reflect the natural frequencies and mode shapes accurately. A model order reduction technique is employed for reducing the finite element structural matrices before developing the controller. Particle swarm based evolutionary optimization technique is used for optimal placement of piezoelectric patch actuators and accelerometer sensors to suppress vibration. H{infty} based active vibration controllers are designed directly in the discrete domain and implemented using dSpace® (DS-1005) electronic signal processing boards. Significant vibration suppression in the multiple bending modes of interest is experimentally demonstrated for sinusoidal and band limited white noise forcing functions.
Resumo:
Following the spirit of the enhanced Russell graph measure, this paper proposes an enhanced Russell-based directional distance measure (ERBDDM) model for dealing with desirable and undesirable outputs in data envelopment analysis (DEA) and allowing some inputs and outputs to be zero. The proposed method is analogous to the output oriented slacks-based measure (OSBM) and directional output distance function approach because it allows the expansion of desirable outputs and the contraction of undesirable outputs. The ERBDDM is superior to the OSBM model and traditional approach since it is not only able to identify all the inefficiency slacks just as the latter, but also avoids the misperception and misspecification of the former, which fails to identify null-jointness production of goods and bads. The paper also imposes a strong complementary slackness condition on the ERBDDM model to deal with the occurrence of multiple projections. Furthermore, we use the Penn Table data to help us explore our new approach in the context of environmental policy evaluations and guidance for performance improvements in 111 countries.
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To mitigate the effects of climate change, countries worldwide are advancing technologies to reduce greenhouse gas emissions. This paper proposes and measures optimal production resource reallocation using data envelopment analysis. This research attempts to clarify the effect of optimal production resource reallocation on CO2 emissions reduction, focusing on regional and industrial characteristics. We use finance, energy, and CO2 emissions data from 13 industrial sectors in 39 countries from 1995 to 2009. The resulting emissions reduction potential is 2.54 Gt-CO2 in the year 2009, with former communist countries having the largest potential to reduce CO2 emissions in the manufacturing sectors. In particular, basic material industry including chemical and steel sectors has a lot of potential to reduce CO2 emissions.
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Volatile organic compounds (VOCs) in the headspace of bubble chambers containing branches of live coral in filtered reef seawater were analysed using gas chromatography with mass spectrometry (GC-MS). When the coral released mucus it was a source of dimethyl sulfide (DMS) and isoprene; however, these VOCs were not emitted to the chamber headspace from mucus-free coral. This finding, which suggests that coral is an intermittent source of DMS and isoprene, was supported by the observation of occasional large pulses of atmospheric DMS (DMSa) over Heron Island reef on the southern Great Barrier Reef (GBR), Australia, in the austral winter. The highest DMSa pulse (320 ppt) was three orders of magnitude less than the DMS mixing ratio (460 ppb) measured in the headspace of a dynamically purged bubble chamber containing a mucus-coated branch of Acropora aspera indicating that coral reefs can be strong point sources of DMSa. Static headspace GC-MS analysis of coral fragments identified mainly DMS and seven other minor reduced sulfur compounds including dimethyl disulfide, methyl mercaptan, and carbon disulfide, while coral reef seawater was an indicated source of methylene chloride, acetone, and methyl ethyl ketone. The VOCs emitted by coral and reef seawater are capable of producing new atmospheric particles < 15 nm diameter as observed at Heron Island reef. DMS and isoprene are known to play a role in low-level cloud formation, so aerosol precursors such as these could influence regional climate through a sea surface temperature regulation mechanism hypothesized to operate over the GBR.
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This thesis contains three subject areas concerning particulate matter in urban area air quality: 1) Analysis of the measured concentrations of particulate matter mass concentrations in the Helsinki Metropolitan Area (HMA) in different locations in relation to traffic sources, and at different times of year and day. 2) The evolution of traffic exhaust originated particulate matter number concentrations and sizes in local street scale are studied by a combination of a dispersion model and an aerosol process model. 3) Some situations of high particulate matter concentrations are analysed with regard to their meteorological origins, especially temperature inversion situations, in the HMA and three other European cities. The prediction of the occurrence of meteorological conditions conducive to elevated particulate matter concentrations in the studied cities is examined. The performance of current numerical weather forecasting models in the case of air pollution episode situations is considered. The study of the ambient measurements revealed clear diurnal variation of the PM10 concentrations in the HMA measurement sites, irrespective of the year and the season of the year. The diurnal variation of local vehicular traffic flows seemed to have no substantial correlation with the PM2.5 concentrations, indicating that the PM10 concentrations were originated mainly from local vehicular traffic (direct emissions and suspension), while the PM2.5 concentrations were mostly of regionally and long-range transported origin. The modelling study of traffic exhaust dispersion and transformation showed that the number concentrations of particles originating from street traffic exhaust undergo a substantial change during the first tens of seconds after being emitted from the vehicle tailpipe. The dilution process was shown to dominate total number concentrations. Minimal effect of both condensation and coagulation was seen in the Aitken mode number concentrations. The included air pollution episodes were chosen on the basis of occurrence in either winter or spring, and having at least partly local origin. In the HMA, air pollution episodes were shown to be linked to predominantly stable atmospheric conditions with high atmospheric pressure and low wind speeds in conjunction with relatively low ambient temperatures. For the other European cities studied, the best meteorological predictors for the elevated concentrations of PM10 were shown to be temporal (hourly) evolutions of temperature inversions, stable atmospheric stability and in some cases, wind speed. Concerning the weather prediction during particulate matter related air pollution episodes, the use of the studied models were found to overpredict pollutant dispersion, leading to underprediction of pollutant concentration levels.
Resumo:
Volatile organic compounds (VOCs) affect atmospheric chemistry and thereafter also participate in the climate change in many ways. The long-lived greenhouse gases and tropospheric ozone are the most important radiative forcing components warming the climate, while aerosols are the most important cooling component. VOCs can have warming effects on the climate: they participate in tropospheric ozone formation and compete for oxidants with the greenhouse gases thus, for example, lengthening the atmospheric lifetime of methane. Some VOCs, on the other hand, cool the atmosphere by taking part in the formation of aerosol particles. Some VOCs, in addition, have direct health effects, such as carcinogenic benzene. VOCs are emitted into the atmosphere in various processes. Primary emissions of VOC include biogenic emissions from vegetation, biomass burning and human activities. VOCs are also produced in secondary emissions from the reactions of other organic compounds. Globally, forests are the largest source of VOC entering the atmosphere. This thesis focuses on the measurement results of emissions and concentrations of VOCs in one of the largest vegetation zones in the world, the boreal zone. An automated sampling system was designed and built for continuous VOC concentration and emission measurements with a proton transfer reaction - mass spectrometer (PTR-MS). The system measured one hour at a time in three-hourly cycles: 1) ambient volume mixing-ratios of VOCs in the Scots-pine-dominated boreal forest, 2) VOC fluxes above the canopy, and 3) VOC emissions from Scots pine shoots. In addition to the online PTR-MS measurements, we determined the composition and seasonality of the VOC emissions from a Siberian larch with adsorbent samples and GC-MS analysis. The VOC emissions from Siberian larch were reported for the fist time in the literature. The VOC emissions were 90% monoterpenes (mainly sabinene) and the rest sesquiterpenes (mainly a-farnesene). The normalized monoterpene emission potentials were highest in late summer, rising again in late autumn. The normalized sesquiterpene emission potentials were also highest in late summer, but decreased towards the autumn. The emissions of mono- and sesquiterpenes from the deciduous Siberian larch, as well as the emissions of monoterpenes measured from the evergreen Scots pine, were well described by the temperature-dependent algorithm. In the Scots-pine-dominated forest, canopy-scale emissions of monoterpenes and oxygenated VOCs (OVOCs) were of the same magnitude. Methanol and acetone were the most abundant OVOCs emitted from the forest and also in the ambient air. Annually, methanol and mixing ratios were of the order of 1 ppbv. The monoterpene and sum of isoprene 2-methyl-3-buten-2-ol (MBO) volume mixing-ratios were an order of magnitude lower. The majority of the monoterpene and methanol emissions from the Scots-pinedominated forest were explained by emissions from Scots pine shoots. The VOCs were divided into three classes based on the dynamics of the summer-time concentrations: 1) reactive compounds with local biological, anthropogenic or chemical sources (methanol, acetone, butanol and hexanal), 2) compounds whose emissions are only temperaturedependent (monoterpenes), 3) long-lived compounds (benzene, acetaldehyde). Biogenic VOC (methanol, acetone, isoprene MBO and monoterpene) volume mixing-ratios had clear diurnal patterns during summer. The ambient mixing ratios of other VOCs did not show this behaviour. During winter we did not observe systematical diurnal cycles for any of the VOCs. Different sources, removal processes and turbulent mixing explained the dynamics of the measured mixing-ratios qualitatively. However, quantitative understanding will require longterm emission measurements of the OVOCs and the use of comprehensive chemistry models. Keywords: Hydrocarbons, VOC, fluxes, volume mixing-ratio, boreal forest
Resumo:
The Australian government has recently pledged a reduction in GHGs emissions of 26–28% below the 2005 level by 2030. How big is the challenge for the country to achieve this target in terms of its present emissions profile, recent historical trends, and the contributions to those trends from key proximate factors contributing to emissions? In this paper, we attempt a quantitative judgement of the challenge by using decomposition analysis. Based on the analysis it appears the announced target will be quite challenging to achieve if the average annual mitigating effects from economic restructuring, energy efficiency improvements and movement towards less emissions-intensive energy sources in evidence over 2002–2013 continued through to 2030; however, if the contribution from these mitigating sources in evidence over 2006–2013 can be sustained, achievement of the target will be much less challenging. The challenge for government then will be to provide a policy framework to ensure the more pronounced beneficial impacts of the mitigating factors evidenced during 2006–2013 can be maintained over the years to 2030.