Alternative Fuels for Transportation

Exploring how to counteract the world's energy insecurity and environmental pollution, this volume covers the production methods, properties, storage, engine tests, system modification, transportation and distribution, economics, safety aspects, applications, and material compatibility of alternative fuels. The esteemed editor highlights the importance of moving toward alternative fuels and the problems and environmental impact of depending on petroleum products. Each self-contained chapter focuses on a particular fuel source, including vegetable oils, biodiesel, methanol, ethanol, dimethyl ether, liquefied petroleum gas, natural gas, hydrogen, electric, fuel cells, and fuel from nonfood crops

Phytosampling of Ambient Air Particulate Matter (PM) -New Method of PM-Associated Pollution Characterization

Ambient air particulate matter (PM) has been documented to be a contributor to a lot of pollution-related health effects. Due to the common anthropogenic origin, PM could be an effective vehicle to carry and deliver many toxic materials, including environmentally persistent free radicals (EPFRs) and polycyclic aromatic hydrocarbons (PAHs) into the human body, thus significantly raise the health risk of PM exposure. Studies of ambient air PM potentially bear artifacts stemming from the collection methods. We investigated the effects of collection methods on the ambient air PM composition and developed a static collection method relying on the particle entrapment by the plant’s leaf through electrostatic interactions and surface trichomes (“phytosampling”). This method allows for easy particle recovery from the matrix, collection under natural environmental conditions, and enables a dense collection network to represent spatial pollutants distribution more accurately. The experimental results show that the new “phytosampling” method is an effective method to collect PM from ambient air. And the PM retrieving process does not compromise the leaf integrity. On phytosampling collected PM, we detected relatively more potassium and calcium, the larger contribution of oxygen-centered EPFRs, different decay behavior, more consistent PAHs distribution between PM sizes, and less toxicological effects in cell viability test compared to the standard sampling method PM samples. These results indicate that the phytosampling method could prevent some unpredictable changes during PM collection, and collected PM will be more representative as the PM that the general public is exposed to. However, phytosampling cannot evaluate the absolute PM concentration in the air, so it serves as an excellent supplementary tool to work in conjunction with the standard PM collection method. This method has been successfully applied to field studies

Chemical kinetics modelling of combustion processes in SI engines

The need for improving the efficiency and reducing emissions is a constant challenge in combustion engine design. For spark ignition engines, these challenges have been targeted in the past decade or so, through ‘engine downsizing’ which refers to a reduction in engine displacement accompanied by turbocharging. Besides the benefits of this, it is expected to aggravate the already serious issue of engine knock owing to increased cylinder pressure. Engine knock which is a consequence of an abnormal mode of combustion in SI engines, is a performance limiting phenomenon and potentially damaging to the engine parts. It is therefore of great interest to develop capability to predict autoignition which leads to engine knock. Traditionally, rather rudimentary skeletal chemical kinetics models have been used for autoignition modelling, however, they either produce incorrect predictions or are only limited to certain fuels. In this work, realistic chemical kinetics of gasoline surrogate oxidation has been employed to address these issues. A holistic modelling approach has been employed to predict combustion, cyclic variability, end gas autoignition and knock propensity of a turbocharged SI engine. This was achieved by first developing a Fortran code for chemical kinetics calculations which was then coupled with a quasi-dimensional thermodynamic combustion modelling code called LUSIE and the commercial package, GT-Power. The resulting code allowed fast and appreciably accurate predictions of the effects of operating condition on autoignition. Modelling was validated through comparisons with engine experimental data at all stages. Constant volume chemical kinetics modelling of the autoignition of various gasoline surrogate components, i.e. iso-octane, n-heptane, toluene and ethanol, by using three reduced mechanisms revealed how the conversion rate of relatively less reactive blend components, toluene and ethanol, is accelerated as they scavenge active radical formed during the oxidation of n-heptane and iso-octane. Autoignition modelling in engines offered an insight into the fuel-engine interactions and that how the composition of a gasoline surrogate should be selected. The simulations also demonstrated the reduced relevance of research and motor octane numbers to the determination of gasoline surrogates and that it is crucial for a gasoline surrogate to reflect the composition of the target gasoline and that optimising its physicochemical properties and octane numbers to match those of the gasoline does not guarantee that the surrogate will mimic the autoignition behaviour of gasoline. During combustion modelling, possible deficiencies in in-cylinder turbulence predictions and possible inaccuracies in turbulent entrainment velocity model required an optimisation of the turbulent length scale in the eddy burn-up model to achieve the correct combustion rate. After the prediction of a correct mean cycle at a certain engine speed, effects of variation in intake air temperature and spark timing were studied without the need for any model adjustment. Autoignition predictions at various conditions of a downsized, turbocharged engine agreed remarkably well with experimental values. When coupled with a simple cyclic variability model, the autoignition predictions for the full spectrum of cylinder pressures allowed determination of a percentage of the severely autoigniting cycles at any given spark timing or intake temperature. Based on that, a knock-limited spark advance was predicted within an accuracy of 2° of crank angle