946 resultados para diesel emissions
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Conversion of agricultural biomass such as wood chips, wheat straw and forest residue for the production of fuels can help in reducing GHG emissions since they are considered as nearly carbon neutral. Around the world there is a significant amount of forest and agricultural-biomass available which could be used for the production of liquid fuels that can be blended with the petroleum-based diesel. Oxymethylene ethers (OMEs) can be derived from biomass via gasification, water-gas shift reaction and methanol production. The addition of OMEs to conventional diesel fuel has great potential to reduce soot formation during the combustion in diesel engines. Unlike methanol and dimethyl ether (DMM) which can also reduce soot formation, the physical properties of OMEs allow the use in modern diesel engines without significant change of the engines infrastructure. In this study, a detailed and data intensive process simulation model was developed to simulate all the unit operations involved in the production of OMEs from biomass. The unit operation considered include biomass drying, gasification, gas cleaning, water gas shift reaction, methanol production and OMEs synthesis. The simulation results were then utilized to conduct a detailed techno-economic assessment study of the whole biomass conversion chain to determine the most attractive pathways for OMEs production. Our recent study shows that the key parameters affecting the OMEs production are equivalence ratio, H2/CO ratio and optimal air flow. Overall, the cost of production ($/liter) of OMEs from different biomass feedstock in Alberta will be determined
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Potential risks of a secondary formation of polychlorinated dibenzodioxins/furans (PCDD/Fs) were assessed for two cordierite-based, wall-through diesel particulate filters (DPFs) for which soot combustion was either catalyzed with an iron- or a copper-based fuel additive. A heavy duty diesel engine was used as test platform, applying the eight-stage ISO 8178/4 C1 cycle. DPF applications neither affected the engine performance, nor did they increase NO, NO2, CO, and CO2 emissions. The latter is a metric for fuel consumption. THC emissions decreased by about 40% when deploying DPFs. PCDD/F emissions, with a focus on tetra- to octachlorinated congeners, were compared under standard and worst case conditions (enhanced chlorine uptake). The iron-catalyzed DPF neither increased PCDD/F emissions, nor did it change the congener pattern, even when traces of chlorine became available. In case of copper, PCDD/F emissions increased by up to 3 orders of magnitude from 22 to 200 to 12 700 pg I-TEQ/L with fuels of < 2, 14, and 110 microg/g chlorine, respectively. Mainly lower chlorinated DD/Fs were formed. Based on these substantial effects on PCDD/F emissions, the copper-catalyzed DPF system was not approved for workplace applications, whereas the iron system fulfilled all the specifications of the Swiss procedures for DPF approval (VERT).
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Rate coefficients for reactions of nitrate radicals (NO3) with the anthropogenic emissions 2-methylpent-2-ene, (Z)-3-methylpent-2-ene.. ethyl vinyl ether, and the stress-induced plant emission ethyl vinyl ketone (pent-1-en-3-one) were determined to be (9.3 +/- 1.1) x 10(-12), (9.3 +/- 3.2) x 10(-12), (1.7 +/- 1.3) x 10(-12) and (9.4 + 2.7) x 10(-17) cm(3) molecule(-1) s(-1). We performed kinetic experiments at room temperature and atmospheric pressure using a relative-rate technique with GC-FID analysis. Experiments with ethyl vinyl ether required a modification of our established procedure that might introduce additional uncertainties, and the errors suggested reflect these difficulties. Rate coefficients are discussed in terms of electronic and steric influences. Atmospheric lifetimes with respect to important oxidants in the troposphere were calculated. NO3-initiated oxidation is found to be the strongly dominating degradation route for 2-methylpent-2-ene, (Z)-3-methylpent-2-ene and ethyl vinyl ether. Atmospheric concentrations of the alkenes and their relative contribution to the total NMHC emissions from trucks can be expected to increase if plans for the introduction of particle filters for diesel engines are implemented on a global scale. Thus more kinetic data are required to better evaluate the impact of these emissions.
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This work was motivated by the importance of conducting a study of vehicle emissions in captive fleets with diesel engine, coupled with the predictive maintenance plan. This type of maintenance includes techniques designed to meet the growing market demand to reduce maintenance costs by increasing the reliability of diagnoses, which has increased interest in automated predictive maintenance on diesel engines, preventing problems that might evolve into routine turn into serious situations, solved only with complex and costly repairs, the Reliability Centered Maintenance, will be the methodology that will make our goal is reached, beyond maintaining the vehicles regulated as fuel consumption and emissions. To Therefore, technical improvements were estimated capable of penetrating the automotive market and give the inshore fleet emission rates of opacity of the vehicles, being directly related to the conditions of the lubricating oil thus contributing to reducing maintenance costs by contributing significantly to emissions of pollutants and an improvement in the air in large cities. This criterion was adopted and implemented, em 241 buses and produced a diagnosis of possible failures by the correlation between the characterization of used lubricating oils and the analysis of opacity, with the objective of the aid the detection and solution of failures for the maintenance of sub-systems according to design criteria, and for this to be a deductive methodology to determine potential causes of failures, has been automated to implement a predictive maintenance system for this purpose was used in our study a mobile unit equipped with a opacimeter and a kit for collection and analysis of lubricating oil and the construction of the network diagnostics, we used a computer program in Microsoft Office Access 2007 platform tool is indispensable for creating a database data, this method is being used and successfully implemented in seven (7) bus companies from the city of Natal (RN) Brazil
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The industry, over the years, has been working to improve the efficiency of diesel engines. More recently, it was observed the need to reduce pollutant emissions to conform to the stringent environmental regulations. This has attached a great interest to develop researches in order to replace the petroleum-based fuels by several types of less polluting fuels, such as blends of diesel oil with vegetable oil esters and diesel fuel with vegetable oils and alcohol, emulsions, and also microemulsions. The main objective of this work was the development of microemulsion systems using nonionic surfactants that belong to the Nonylphenols ethoxylated group and Lauric ethoxylated alcohol group, ethanol/diesel blends, and diesel/biodiesel blends for use in diesel engines. First, in order to select the microemulsion systems, ternary phase diagrams of the used blends were obtained. The systems were composed by: nonionic surfactants, water as polar phase, and diesel fuel or diesel/biodiesel blends as apolar phase. The microemulsion systems and blends, which represent the studied fuels, were characterized by density, viscosity, cetane number and flash point. It was also evaluated the effect of temperature in the stability of microemulsion systems, the performance of the engine, and the emissions of carbon monoxide, nitrogen oxides, unburned hydrocarbons, and smoke for all studied blends. Tests of specific fuel consumption as a function of engine power were accomplished in a cycle diesel engine on a dynamometer bench and the emissions were evaluated using a GreenLine 8000 analyzer. The obtained results showed a slight increase in fuel consumption when microemulsion systems and diesel/biodiesel blends were burned, but it was observed a reduction in the emission of nitrogen oxides, unburned hydrocarbons, smoke index and f sulfur oxides
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The use of biodiesel is increasing as an attractive fuel due to the depleting fossil fuel resources and environmental degradation. This paper presents results of an investigation on the potentials of biodiesel as an alternative fuel and main substitute of diesel oil, comparing the CO2 emissions of the main fuels in the Brazilian market with those of biodiesel, in pure form or blended in different proportions with diesel oil (2%, 5%, and 20%, called B2, B5, and B20, respectively). The results of the study are shown in ton CO2 per m(3) and ton CO2 per year of fuel. The fuels were analyzed considering their chemical composition, stoichiometric combustion parameters and mean consumption for a single vehicle. The fuels studied were: gasoline, diesel oil, anhydrous ethyl alcohol (anhydrous ethanol), and biodiesel from used frying oil and from soybean oil. For the case of biodiesel, its complete life cycle and the closed carbon cycle (photosynthesis) were considered. With data provided by the Brazilian Association of Automotive Vehicle Manufacturers (ANFAVEA) for the number of vehicles produced in Brazil, the emissions of CO2 for the national fleet in 2007 were obtained per type of fuel. With data provided by the Brazilian Department of Transit (DENATRAN) concerning the number of diesel vehicles in the last five years in Brazil, the total CO2 emissions and the percentage that they would decrease in the case of use of pure biodiesel, B100, or several mixtures, B2, B5 and B20, were calculated. Estimates of CO2 emissions for a future scenario considering the mixtures B5 and B20 are also included in this article. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.
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Pós-graduação em Engenharia Mecânica - FEG
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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In this study, particulate matter (PM) were characterized from a place impacted by heavy-duty vehicles (Bus Station) fuelled with diesel/biodiesel fuel blend (B3) in the city of Londrina, Brazil. Sixteen priority polycyclic aromatic hydrocarbons (PAH) concentrations were analyzed in the samples by their association with atmospheric PM, mass size distributions and major ions (fluorite, chloride, bromide, nitrate, phosphate, sulfate, nitrite, oxalate; fumarate, formate, succinate and acetate; lithium, sodium, potassium, magnesium, calcium and ammonium). Results indicate that major ions represented 21.2% particulate matter mass. Nitrate, sulfate, and ammonium, respectively, presented the highest concentration levels, indicating that biodiesel may also be a significant source for these ions, especially nitrate. Dibenzo[a,h]anthracene and indeno[1,2,3,-cd]pyrene were the main PAH found, and a higher fraction of PAH particles was found in diameters lower than 0.25 mu m in Londrina bus station. The fine and ultrafine particles were dominant among the PM evaluated, suggesting that biodiesel decreases the total PAH emission. However, it does also increase the fraction of fine and ultrafine particles when compared to diesel.
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In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM2.5 samples, employing gravimetry to determine PM2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 mu g/m(3), respectively. In Sao Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM2.5 mass. We used receptor models to identify distinct source-related PM2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-a-vis health care costs.
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The Department of Mechanical and Civil Engineering (DIMeC) of the University of Modena and Reggio Emilia is developing a new type of small capacity HSDI 2-Stroke Diesel engine (called HSD2), featuring a specifically designed combustion system, aimed to reduce weight, size and manufacturing costs, and improving pollutant emissions at partial load. The present work is focused on the analysis of the combustion and the scavenging process, investigated by means of a version of the KIVA-3V code customized by the University of Chalmers and modified by DIMeC. The customization of the KIVA-3V code includes a detailed combustion chemistry approach, coupled with a comprehensive oxidation mechanism for diesel oil surrogate and the modeling of turbulence/chemistry interaction through the PaSR (Partially Stirred Reactor) model. A four stroke automobile Diesel engine featuring a very close bore size is taken as a reference, for both the numerical models calibration and for a comparison with the 2-Stroke engine. Analysis is carried out trough a comparison between HSD2 and FIAT 1300 MultiJet in several operating conditions, at full and partial load. Such a comparison clearly demonstrates the effectiveness of the two stroke concept in terms of emissions reduction and high power density. However, HSD2 is still a virtual engine, and experimental results are needed to assume the reliability of numerical results.
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This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.
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This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.