Jet fuels produced from sources other than petroleum are receiving considerable attention because they offer the potential to diversify energy supplies while mitigating the net environmental impacts of aviation. The hydroprocessed esters and fatty acids (HEFA) process is a commercially deployed technology that converts vegetable oils and animal fats from triglycerides into hydrocarbons suitable for use in diesel and jet fuels. The technical means of producing alternative fuels from renewable oils, and the resulting carbon intensity has been documented in previous work. However, the cost of production is not available in the literature. This work reviews HEFA fuel production, and estimates the gate price of fuel for several plant sizes and operating conditions. Aspen Plus was used to model biorefi nery material and energy balances for unit operations and supporting utilities. A discounted-cash-fl ow-rate-of-return (DCFROR) economic model was used for sensitivity analysis. The gate price was found to range between $1.00 L -1 for a 378 MML yr -1 HEFA facility, and $1.16 L -1 for a 116 MML yr -1 facility. Maximizing jet fuel production ranged between $0.07 and $0.08 L -1 due to increased hydrogen use and decreased diesel and jet fuel yield. While feedstock cost is the most signifi cant portion of fuel cost, facility size, fi nancing, and capacity utilization also infl uence production costs.
The presence of variability in life cycle analysis (LCA) is inherent due to both inexact LCA procedures and variation of numerical inputs. Variability in LCA needs to be clearly distinguished from uncertainty. This paper uses specific examples from the production of diesel and jet fuels from 14 different feedstocks to demonstrate general trends in the types and magnitudes of variability present in life cycle greenhouse gas (LC-GHG) inventories of middle distillate fuels. Sources of variability have been categorized as pathway specific, coproduct usage and allocation, and land use change. The results of this research demonstrate that subjective choices such as coproduct usage and allocation methodology can be more important sources of variability in the LC-GHG inventory of a fuel option than the process and energy use of fuel production. Through the application of a consistent analysis methodology across all fuel options, the influence of these subjective biases is minimized, and the LC-GHG inventories for each feedstock-to-fuel option can be effectively compared and discussed. By considering the types and magnitudes of variability across multiple fuel pathways, it is evident that LCA results should be presented as a range instead of a point value. The policy implications of this are discussed.
This investigation presents a unique and elaborate set of experiments relating the generation of noise to the evolution of large-scale turbulence structures within an ideally expanded, Mach 1.28, high-Reynolds-number (1.03 × 10 6) jet. The results appear to indicate many similarities between the noise generation processes of highspeed low-Reynolds-number and high-speed high-Reynolds-number jets. Similar to the rapid changes observed in the region of noise generation in low-Reynoldsnumber jets in previous experimental and computational work, a series of robust flow features formed approximately one convective time scale before noise emission and then rapidly disintegrated shortly before the estimated moment of noise emission. Coincident with the disintegration, a positive image intensity fluctuation formed at the jet centreline in a region that is immediately past the end of the potential core. This indicates mixed fluid had reached the jet core. These results are consistent with the formation of large-scale structures within the shear layer, which entrain ambient air into the jet, and their eventual interaction and disintegration apparently result in noise generation. These results are quite different from the evolution of the jet during prolonged periods that lacked significant sound emission. The observations presented in this work were made through the use of well-established techniques that were brought together in an unconventional fashion. The sources of large-amplitude sound waves were estimated in time and three-dimensional space using a novel microphone array/beamforming algorithm while the noise-generation region of the mixing layer was simultaneously visualized on two orthogonal planes (one of which was temporally resolved). The flow images were conditionally sampled based on whether or not a sound wave was created within the region of the flow while it was being imaged and a series of images was compiled that was roughly phase-locked onto the moment of sound emission. Another set of images was gathered based on a lack of sound waves reaching the microphone array over several convective time scales. Proper orthogonal decomposition (POD) was then used to create a basis for the flow images and this basis was used to reconstruct the evolution of the jet.
Considerable research and development is underway to produce fuels from microalgae, one of several options being explored for increasing transportation fuel supplies and mitigating greenhouse gas emissions (GHG). This work models life-cycle GHG and on-site freshwater consumption for algal biofuels over a wide technology space, spanning both near- and long-term options. The environmental performance of algal biofuel production can vary considerably and is influenced by engineering, biological, siting, and land-use considerations. We have examined these considerations for open pond systems, to identify variables that have a strong influence on GHG and freshwater consumption. We conclude that algal biofuels can yield GHG reductions relative to fossil and other biobased fuels with the use of appropriate technology options. Further, freshwater consumption for algal biofuels produced using saline pond systems can be comparable to that of petroleum-derived fuels.
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