Co-processing biogenic feedstocks in oil refineries will reduce the greenhouse gas emissions normally associated with fossil-derived transportation fuels. The fluid catalytic cracker (FCC) within a refinery is a robust processing unit and will probably be a preferred insertion point if biocrudes, produced by the liquefaction of biomass, are co-processed within a refinery. Fluid catalytic cracking results in a wide range of intermediate products which can be upgraded to gasoline, diesel, heavy fuel oil and liquified petroleum gas blendstocks. Coke is also produced and provides heating for feedstocks, the endothermic catalytic cracking reactions and the regeneration of the FCC catalyst. However, coke combustion also generates carbon dioxide and is a significant source of refinery greenhouse gas emissions. As detailed here, the continuous nature of the process makes the physical evaluation of any biogenic coke fraction, via methods such as C14 isotope analysis, quite challenging. However, quantifying the stack gases provides one way of assessing the renewable content of the carbon dioxide derived from coke combustion. The hourly data from 1 year of commercial operation was assessed using linear and Bayesian ridge regression to quantify the burning coefficient of the coke when co-processing lipids at the FCC.
Enhanced biosurfactant production by Corynebacterium alkanolyticum ATCC 21511 was accomplished in a self-cycling fermenter (SCF) on a hexadecane substrate. The phospholipid biosurfactant produced during each cycle could be monitored rapidly using fluorescence spectroscopy. By optimizing the cycling pattern of the SCF, significantly better yields of biosurfactant were obtained than previously reported for this microorganism. It was also possible to virtually eliminate the hydrocarbon residue in the product. Harvest concentrations of 1.9 g L −1 were obtained by using a two-stage fermentation. The first step was the growth of C. alkanolyticum in an SCF to yield a harvest of synchronous cells. These cells were transferred to a second vessel for the production stage. The concentration of biosurfactant could be further increased to 2.7 g L −1 by the addition of more hexadecane at the beginning of the second stage.The recent interest in industrial applications of biosurfactants has been driven by the biodegradability and broad applicability of these microbial surface-active compounds (1-5). The wide range of chemical structures and their effectiveness over a broad range of temperature and pH make biosurfactants appropriate for use in fields as diverse as oil-spill remediation, food processing, and cosmetics.A key factor hindering the widespread use of biosurfactants is that microorganisms generally produce these compounds in very small quantities. Although there are a few examples of large yields of sophorolipids (6,7), the concentrations of most biosurfactants are so low (8-13) that the recovery of these biosurfactants is both difficult and expensive (2,4,5,14,15).Previous work with Corynebacterium alkanolyticum showed that this organism produces a phospholipid biosurfactant in yields of 0.5 to 0.7 g L −1 (13). In this study, the same microorganism was grown in a self-cycling fermenter (SCF). The SCF has demonstrated enhanced yields for several biological products. The SCF technique has been described previously (16-19), but because it has several unusual features, it is useful to summarize the main features of its operation.Self-cycling fermentation is a computer-controlled series of batch growth cycles. A parameter related to growth, such as the concentration of dissolved oxygen (DO) in the growth medium, is monitored constantly. As growth proceeds, the DO gradually decreases in response to the demand from the cells. At some point, the limiting nutrient is completely consumed and there is a sharp decrease in growth rate. This results in an immediate increase in the DO as the cells are no longer removing oxygen as quickly as it is being added to the medium. The computer monitoring the DO recognizes the resulting minimum and starts a series of procedures with the result that half of the working volume in the fermenter is harvested and then this volume is replaced with an equal amount of fresh medium. With the replenished nutrients, growth immediately resumes, the DO starts to decrease, and the cycle is repeated. This t...
Self-cycling fermentation (SCF) was coupled with a genetic algorithm (GA) to provide a simple system for evaluating biological models. The SCF provided the necessary system excitation and data "richness" required to completely define the fitted biological models. The solution scheme based on the GA avoided the computational difficulties often associated with calculusbased nonlinear regression techniques, resulting in rapid and accurate convergence. After validating the mathematical approach, data from the SCF obtained under denitrifying conditions were fitted successfully to an established model using the GA. Finally, data obtained in the SCF for the removal of phenol were used to compare multiple models. This work suggests that the SCF, in conjunction with the GA, provides a coherent system that can facilitate the characterization of biological systems.
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