3 resultados para Diesel Fuel.

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The removal of aromatic hydrocarbons from diesel has received considerable attention after environmental regulations that require petroleum refiners to raise cetane number and to limit aromatics in diesel fuel in order to improve combustion efficiency and reduce particulate and NOx emissions. An alternative is blending with Fischer–Tropsch (FT) gas-to-liquid diesel fuel; however, this option may not be economically viable solution in case of extensive blend. Another alternative is to incorporate in the diesel pool a greater fraction of the so-called light cycle oil (LCO). Due to its high aromatics content and its low cetane number (typically between 20 and 30), the incorporation of LCO may have a negative impact on the quality of diesel. Current technologies for LCO improvement are based on hydrogenation to adjust both sulphur and cetane number but while an important fraction of the aromatics present in LCO can be saturated in a deep hydrogenation process, the cetane number may still be lower than the target values specified in diesel legislations, so further upgrading is needed. An interesting technology for improving the cetane number of diesels and maintaining meanwhile high diesel yields is achieved by combining a complete hydrogenation process with a selective ring opening (SRO) reaction of the naphthenic rings. The SRO can be defined as naphthene ring-opening to form compounds with high cetane number, but without any carbon losses. Controlling the interconversion of six- and five- membered rings via an acid-catalyzed ring-contraction step is also of great importance, since selective conversion of six-membered to five-membered naphthene rings greatly influences ring-opening rates and selectivity. High intrinsic activity may be enhanced by deposition of noble metals on acidic, high surface area supports, because it is possible to arrange close proximity of the metal and acid sites. Moreover, in large-pore supports, the diffusion resistance of liquid reactants into the pores is minimized. In addition to metal centres, the acid sites of support also plays role in aromatics hydrogenation. However, the functions of different kinds of acid sites (Brønsted vs. Lewis acidity), and their optimal concentrations and strengths, remain unclear. In the present study we investigated the upgrading of an aromatic-rich feedstock over different type of metal supported on mesoporous silica-alumina. The selective hydrogenolysis and ring opening of tetrahydronaphthalene (THN or tetralin) was carried out as representative of LCO fractions after deep hydrogenation process. In this regards the aim of this study is to evaluate both the effect of metals and that of the supports characterized by different acid distribution and strength, on conversion and selectivity. For this purpose a series of catalysts were prepared by impregnation. The catalysts were characterized and conversion tests of THN were performed in a lab-scale plant operating in the pressure range from 7.0-5.0 MPa and in the temperature range from 300 to 360°C.

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Enzyveba, a partially characterized complex consortium of not-adapted microorganisms developed through prolonged stabilization of organic wastes, was found to markedly intensify the aerobic remediation of aged PAH- and PCB-contaminated soil by acting as a source of exogenous specialized microorganisms and nutrients. Thus, Enzyveba was tested in the bioremediation of Diesel (G1) and HiQ Diesel (G2) contaminated soils under aerobic slurry-phase conditions by means of a chemical, microbiological, ecotoxicological integrated analytical procedure. The addition of Enzyveba resulted in a higher availability of cultivable specialized bacteria and fungi but this resulted in a slight intensification of soil remediation, probably because of the high content of nutrients and specialized microorganisms of the soil. In many cases, the biotreatability of soils impacted by diesel fuel is limited by their poor content of autochthonous pollutant-degrading microorganisms. Thus, bioaugmentation with stable and reproducible cultures with the required broad substrate specificity might be the solution for a successful remediation. Two microbial consortia, ENZ-G1 and ENZ-G2, were enriched from Enzyveba on G1 and G2. Both consortia consist of a similar composition of bacterial and fungal species. They exhibited a comparable and significant biodegradation capability by removing about 90% of 1 g/l of diesel fuel under liquid culture conditions. Given their remarkable biodegradation potential, richness of quite diverse microbes, stability and resistance after cryopreservation at -20 °C for several months, both consortia appear very interesting candidates for bioaugmentation on site. The mycoflora of a soil historically contaminated by high concentration of PCBs was characterised before, at the beginning and at the end of the biotreatment mentioned above. Several mitosporic fungi isolated from soil grew in presence of a mixture of three PCBs congeners when also glucose was provided. This is the first study in which 5 strains of mitosporic species able to biodegrade PCB are reported in the literature.

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DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.