No description available.

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 65).

No description available.

Thesis--Auburn University, 2010. / Abstract. Includes bibliographic references (p.111-129).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 60-67).

New federal legislation proposes to reduce greenhouse gas (GHG) emissions associated with biofuel production. To comply, existing corn ethanol plants will have to invest in new more carbon efficient production technology such as dry fractionation. However, this will be challenging for the industry given the present financial environment of surplus production, recent profit declines, numerous bankruptcies, and lender imposed covenants. This study examines a dry-mill ethanol firm's ability to invest in dry fractionation technology in the face of declining profitability and stringent lender cash flow repayment constraints. Firm level risk aversion also is considered when determining a firm's willingness to invest in dry fractionation technology. A Monte Carlo simulation model is constructed to estimate firm profits, cash flows, and changes in equity following new investment in fractionation to determine an optimal investment strategy. The addition of a lender-imposed sweep, whereby a percentage of free cash flow is used to pay off extra debt in high profit years, reduces the firm's ability to build equity and increases bankruptcy risk under investment. However, the sweep increases long-run equity because total financing costs are reduced with accelerated debt repayment. This thesis shows that while ethanol firm profits are uncertain, the lender's imposition of a sweep combined with increased profit from dry fractionation technology help the firm increase long-run financial resiliency.

Algae are primary producers in aquatic ecosystems and are thus the most important organisms in maintaining ecosystem functioning and stability. The usage of algae by humans is quite extensive; they act as an ingredient in aquaculture feed, a potential biomedical resource, as a fertiliser and as a nutritional source. Recently, algae have been identified as a third generation biofuel feedstock for fuel generation which essentially means that algae are more efficient, net carbon neutral and have less impacts on the environment. Algae as organisms are extremely sensitive to changes in the immediate environment. The interaction of parameters with each other causes minute changes in the environment which may alter the algae biomass present and the lipids that can be extracted from the biomass. The focus of this study is to model and determine which conditions maximise algal biomass and the subsequent lipids that can be extracted from the biomass. This will allow biofuel producers to understand which conditions are the best for harvesting algae in artificial conditions or harvesting algae from the wild. Furthermore, the model developed has broad application for biofuel specialists, pollution remediation specialists and biologists. This model developed is able to determine the present state of the algal bloom and uses the present state to predict the future state of bloom hence determining the optimal conditions to harvest. The model was developed under optimal ranges described by the Food and Agriculture Organisation (FAO) and designed to replicate the most common combinations of parameters present in the wild. For the purposes of this study, various combinations of parameters within their optimal ranges that is temperature (18 – 24°C), salinity (20 – 24 p.p.t.) and photoperiod (25 – 75% light exposure) were assessed. The model was run for 72 hours with sampling every 6 hours. Every six hours, algal growth was measured by the biomass present (chloro-pigments used as estimators); this was done by fluorescence. Lipids were then extracted from algal biomass using the Bligh and Dyer method (1959). Spline curves were fitted to the data and analysis performed using Mathematica 8.0. It was found that photoperiod was the most important variable in controlling algal growth. Furthermore, lipids extracted from biomass were at their highest when algae were exposed to the conditions 75% light exposure, 21°C and 22 p.p.t. These conditions would allow for the highest amount of biofuel to be produced. Generally, algae biomass trend graphs mimic lipid trend graphs over the 72 hour period that is when lipids are at their maximum, biomass concentrations are at their maximum. It can be concluded from time model that the best time to harvest biomass is 48 hours from the initial start time of algal growth to gain the highest amount of lipids for biofuel production. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2012.

Thesis (Ph. D. - Arid Lands Resource Sciences)--University of Arizona, 1983. / Includes bibliographical references (leaves 164-170).

The sugar beet (Beta vulgaris) plant has in recent years been added to the Biofuel Industrial Strategy (Department of Minerals and Energy, 2007) by the South African government as a crop grown for the production of bio-ethanol. Sugar beet is commonly grown in Europe for the production of sucrose and has recently been cultivated in Cradock and the surrounding areas (Engineering News, 2008). The biofuel industry usually ferments the sucrose with Saccharomyces cerevisiae to yield bio-ethanol. However, researchers are presented with a critical role to increase current yields as there are concerns over the process costs from industrial biotechnologists. The beet factories produce a pulp by-product removed of all sucrose. The hemicellulose-rich pulp can be degraded by microbial enzymes to simple sugars that can be subsequently fermented to bio-ethanol. Thus, the pulp represents a potential source for second generation biofuel. The process of utilising microbial hemicellulases requires an initial chemical pre-treatment step to delignify the sugar beet pulp (SBP). An alkaline pre-treatment with ‘slake lime’ (calcium hydroxide) was investigated using a 23 factorial design and the factors examined were: lime load; temperature and time. The analysed results showed the highest release of reducing sugars at the pre-treatment conditions of: 0.4 g lime / g SBP; 40°C and 36 hours. A partial characterisation of the Clostridium cellulovorans hemicellulases was carried out to verify the optimal activity conditions stated in literature. The highest release of reducing sugars was measured at pH 6.5 – 7.0 and at 45°C for arabinofuranosidase A (ArfA); at pH 5.5 and 40°C for mannanase A (ManA) and pH 5.0 – 6.0 and 45°C for xylanase A (XynA). Temperature studies showed that a complete loss of enzymatic activity occurred after 11 hours for ManA; and 84-96 hours for ArfA. XynA was still active after 120 hours. The optimised lime pre-treated SBP was subsequently degraded using various combinations and percentages of C. cellulovorans ArfA, ManA and XynA to determine the maximal release of reducing sugars. Synergistically, the highest synergy was observed at 75% ArfA and 25% ManA, with a specific activity of 2.9 μmol/min/g protein. However, the highest release of sugars was observed at 4.2 μmol/min/g protein at 100% ArfA. This study has initiated the research within South Africa on SBP and its degradation by C. cellulovorans. Preliminary studies show that SBP has the potential to be utilised as a second generation biofuel source.

The research reported here explored, a "new" approach to biomass energy conversion for small-scale process heat-applications. The conversion process uses close-coupled catalytic. combustion to burn combustibles in effluent generated by primary combustion or gasification of biomass fuels. Computer control of primary and secondary air flow rates allow control of the devices output power while maintaining fuel-lean or stoichiometric conditions in the effluent entering the catalytic combustion zone. The intent of the secondary combustion system is to ensure "clean" exhaust (i.e., promote complete combustion). A small-scale combustor/gasifier was built and instrumented. Characteristics of combustion were studied for three biomass fuels so that primary and secondary air flow control strategies could be devised. A bang-bang type controller was devised for primary air flow control. Secondary air as controlled based on feedback signals from an inexpensive automobile exhaust gas oxygen sensor. The control strategies and catalytic combustion were implemented on prototype combustor/gasifier and the device was tested with good results. Power turn down ratios of 4 to 1 and 3 to 1 were achieved. The zitconia-type automobile exhaust gas oxygen sensors adapted well to the combustion environment of biomass fuel, at least for short periods (long term durability tests were not conducted). The secondary air control system was able to maintain fuel-lean flows for the most part and, the secondary combustion system provided reductions of approximately three fourths in carbon monoxide emissions. / Master of Science