11 resultados para Greenhouse gas

em Digital Commons - Michigan Tech


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The challenges posed by global climate change are motivating the investigation of strategies that can reduce the life cycle greenhouse gas (GHG) emissions of products and processes. While new construction materials and technologies have received significant attention, there has been limited emphasis on understanding how construction processes can be best managed to reduce GHG emissions. Unexpected disruptive events tend to adversely impact construction costs and delay project completion. They also tend to increase project GHG emissions. The objective of this paper is to investigate ways in which project GHG emissions can be reduced by appropriate management of disruptive events. First, an empirical analysis of construction data from a specific highway construction project is used to illustrate the impact of unexpected schedule delays in increasing project GHG emissions. Next, a simulation based methodology is described to assess the effectiveness of alternative project management strategies in reducing GHG emissions. The contribution of this paper is that it explicitly considers projects emissions, in addition to cost and project duration, in developing project management strategies. Practical application of the method discussed in this paper will help construction firms reduce their project emissions through strategic project management, and without significant investment in new technology. In effect, this paper lays the foundation for best practices in construction management that will optimize project cost and duration, while minimizing GHG emissions.

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Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

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Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

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To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

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In recent years, growing attention has been devoted to the use of lignocellulosic biomass as a feedstock to produce renewable carbohydrates as a source of energy products, including liquid alternatives to fossil fuels. The benefits of developing woody biomass to ethanol technology are to increase the long-term national energy security, reduce fossil energy consumption, lower greenhouse gas emissions, use renewable rather than depletable resources, and create local jobs. Currently, research is driven by the need to reduce the cost of biomass-ethanol production. One of the preferred methods is to thermochemically pretreat the biomass material and subsequently, enzymatically hydrolyze the pretreated material to fermentable sugars that can then be converted to ethanol using specialized microorganisms. The goals of pretreatment are to remove the hemicellulose fraction from other biomass components, reduce bioconversion time, enhance enzymatic conversion of the cellulose fraction, and, hopefully, obtain a higher ethanol yield. The primary goal of this research is to obtain kinetic detailed data for dilute acid hydrolysis for several timber species from the Upper Peninsula of Michigan and switchgrass. These results will be used to identify optimum reaction conditions to maximize production of fermentable sugars and minimize production of non-fermentable byproducts. The structural carbohydrate analysis of the biomass species used in this project was performed using the procedure proposed by National Renewable Energy Laboratory (NREL). Subsequently, dilute acid-catalyzed hydrolysis of biomass, including aspen, basswood, balsam, red maple, and switchgrass, was studied at various temperatures, acid concentrations, and particle sizes in a 1-L well-mixed batch reactor (Parr Instruments, ii Model 4571). 25 g of biomass and 500 mL of diluted acid solution were added into a 1-L glass liner, and then put into the reactor. During the experiment, 5 mL samples were taken starting at 100°C at 3 min intervals until reaching the targeted temperature (160, 175, or 190°C), followed by 4 samples after achieving the desired temperature. The collected samples were then cooled in an ice bath immediately to stop the reaction. The cooled samples were filtered using 0.2 μm MILLIPORE membrane filter to remove suspended solids. The filtered samples were then analyzed using High Performance Liquid Chromatography (HPLC) with a Bio-Rad Aminex HPX-87P column, and refractive index detection to measure monomeric and polymeric sugars plus degradation byproducts. A first order reaction model was assumed and the kinetic parameters such as activation energy and pre-exponential factor from Arrhenius equation were obtained from a match between the model and experimental data. The reaction temperature increases linearly after 40 minutes during experiments. Xylose and other sugars were formed from hemicellulose hydrolysis over this heat up period until a maximum concentration was reached at the time near when the targeted temperature was reached. However, negligible amount of xylose byproducts and small concentrations of other soluble sugars, such as mannose, arabinose, and galactose were detected during this initial heat up period. Very little cellulose hydrolysis yielding glucose was observed during the initial heat up period. On the other hand, later in the reaction during the constant temperature period xylose was degraded to furfural. Glucose production from cellulose was increased during this constant temperature period at later time points in the reaction. The kinetic coefficient governing the generation of xylose from hemicellulose and the generation of furfural from xylose presented a coherent dependence on both temperature and acid concentration. However, no effect was observed in the particle size. There were three types of biomass used in this project; hardwood (aspen, basswood, and red maple), softwood (balsam), and a herbaceous crop (switchgrass). The activation energies and the pre-exponential factors of the timber species and switchgrass were in a range of 49 - 180 kJ/mol and from 7.5x104 - 2.6x1020 min-1, respectively, for the xylose formation model. In addition, for xylose degradation, the activation energies and the preexponential factors ranged from 130 - 170 kJ/mol and from 6.8x1013 - 3.7x1017 min-1, respectively. The results compare favorably with the literature values given by Ranganathan et al, 1985. Overall, up to 92 % of the xylose was able to generate from the dilute acid hydrolysis in this project.

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Biofuels are alternative fuels that have the promise of reducing reliance on imported fossil fuels and decreasing emission of greenhouse gases from energy consumption. This thesis analyses the environmental impacts focusing on the greenhouse gas (GHG) emissions associated with the production and delivery of biofuel using the new Integrated Hydropyrolysis and Hydroconversion (IH2) process. The IH2 process is an innovative process for the conversion of woody biomass into hydrocarbon liquid transportation fuels in the range of gasoline and diesel. A cradle-to-grave life cycle assessment (LCA) was used to calculate the greenhouse gas emissions associated with diverse feedstocks production systems and delivery to the IH2 facility plus producing and using these new renewable liquid fuels. The biomass feedstocks analyzed include algae (microalgae), bagasse from a sugar cane-producing locations such as Brazil or extreme southern US, corn stover from Midwest US locations, and forest feedstocks from a northern Wisconsin location. The life cycle greenhouse gas (GHG) emissions savings of 58%–98% were calculated for IH2 gasoline and diesel production and combustion use in vehicles compared to fossil fuels. The range of savings is due to different biomass feedstocks and transportation modes and distances. Different scenarios were conducted to understand the uncertainties in certain input data to the LCA model, particularly in the feedstock production section, the IH2 biofuel production section, and transportation sections.

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Global warming issue becomes more significant to human beings and other organisms on the earth. Among many greenhouse gases, carbon dioxide (CO2) has the largest contribution to global warming. To find an effective way to utilize the greenhouse gas is urgent. It is the best way to convert CO2 to useful compounds. CO2 reforming of methane is an attractive process to convert CO2 and methane into synthesis gas (CO/H2), which can be used as a feedstock for gasoline, methanol, and other hydrocarbons. Nickel and cobalt were found to have good activity for CO2 reforming. However, they have a poor stability due to carbon deposition. This research developed efficient Ni-Co solid solution catalysts with excellent activities and high stability for CO2 reforming of methane. First, the structure of binary oxide solid solution of nickel and cobalt was investigated. It was found that while the calcination of Ni(NO3)2 and Co(NO3)2 mixture with 1:1 molar ratio at a high temperature above 800 oC generated NiO-CoO solid solution, only Ni3O4-Co3O4 solid solution was observed after the calcination at a low temperature of 500 oC. Furthermore, if the calcination was carried out at a medium temperature arranged from 600 to 700 oC, both NiO-CoO and Ni3O4-Co3O4 solid solutions can be formed. This occurred because Co3O4 can induce the formation of Ni3O4, whereas NiO can stabilize CoO. In addition, the lattice parameter of Ni3O4, which was predicted by using Vegard’s Law, is 8.2054 Å. As a very important part of this dissertation, Ni-Co solid solution was evaluated as catalysts for CO2 reforming of methane. It was revealed that nickel-cobalt solid solution showed excellent catalytic performance and high stability for CO2 reforming of methane. However, the stability of Ni-Co solid solution catalysts is strongly dependent on their composition and preparation condition. The optimum composition is 50%Ni-50%Co. Furthermore, the structure of Ni-Co catalysts was characterized by XRD, Vvis, TPR, TPD, BET, AES, TEM, XANES and EXAFS. The relationship between the structure and the catalytic performance was established: (1) The reduced NiO-CoO solid solution possesses better catalytic performance and stability than the reduced Ni3O4-Co3O4 solid solution. (2) Ni is richer on surface in Ni-Co catalysts. And (3) the reduction of Ni-Co-O solid solution generated two types of particles, small and large particles. The small ones are dispersed on large ones as catalytic component.

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This Ph.D. research is comprised of three major components; (i) Characterization study to analyze the composition of defatted corn syrup (DCS) from a dry corn mill facility (ii) Hydrolysis experiments to optimize the production of fermentable sugars and amino acid platform using DCS and (iii) Sustainability analyses. Analyses of DCS included total solids, ash content, total protein, amino acids, inorganic elements, starch, total carbohydrates, lignin, organic acids, glycerol, and presence of functional groups. Total solids content was 37.4% (± 0.4%) by weight, and the mass balance closure was 101%. Total carbohydrates [27% (± 5%) wt.] comprised of starch (5.6%), soluble monomer carbohydrates (12%) and non-starch carbohydrates (10%). Hemicellulose components (structural and non-structural) were; xylan (6%), xylose (1%), mannan (1%), mannose (0.4%), arabinan (1%), arabinose (0.4%), galatactan (3%) and galactose (0.4%). Based on the measured physical and chemical components, bio-chemical conversion route and subsequent fermentation to value added products was identified as promising. DCS has potential to serve as an important fermentation feedstock for bio-based chemicals production. In the sugar hydrolysis experiments, reaction parameters such as acid concentration and retention time were analyzed to determine the optimal conditions to maximize monomer sugar yields while keeping the inhibitors at minimum. Total fermentable sugars produced can reach approximately 86% of theoretical yield when subjected to dilute acid pretreatment (DAP). DAP followed by subsequent enzymatic hydrolysis was most effective for 0 wt% acid hydrolysate samples and least efficient towards 1 and 2 wt% acid hydrolysate samples. The best hydrolysis scheme DCS from an industry's point of view is standalone 60 minutes dilute acid hydrolysis at 2 wt% acid concentration. The combined effect of hydrolysis reaction time, temperature and ratio of enzyme to substrate ratio to develop hydrolysis process that optimizes the production of amino acids in DCS were studied. Four key hydrolysis pathways were investigated for the production of amino acids using DCS. The first hydrolysis pathway is the amino acid analysis using DAP. The second pathway is DAP of DCS followed by protein hydrolysis using proteases [Trypsin, Pronase E (Streptomyces griseus) and Protex 6L]. The third hydrolysis pathway investigated a standalone experiment using proteases (Trypsin, Pronase E, Protex 6L, and Alcalase) on the DCS without any pretreatment. The final pathway investigated the use of Accellerase 1500® and Protex 6L to simultaneously produce fermentable sugars and amino acids over a 24 hour hydrolysis reaction time. The 3 key objectives of the techno-economic analysis component of this PhD research included; (i) Development of a process design for the production of both the sugar and amino acid platforms with DAP using DCS (ii) A preliminary cost analysis to estimate the initial capital cost and operating cost of this facility (iii) A greenhouse gas analysis to understand the environmental impact of this facility. Using Aspen Plus®, a conceptual process design has been constructed. Finally, both Aspen Plus Economic Analyzer® and Simapro® sofware were employed to conduct the cost analysis as well as the carbon footprint emissions of this process facility respectively. Another section of my PhD research work focused on the life cycle assessment (LCA) of commonly used dairy feeds in the U.S. Greenhouse gas (GHG) emissions analysis was conducted for cultivation, harvesting, and production of common dairy feeds used for the production of dairy milk in the U.S. The goal was to determine the carbon footprint [grams CO2 equivalents (gCO2e)/kg of dry feed] in the U.S. on a regional basis, identify key inputs, and make recommendations for emissions reduction. The final section of my Ph.D. research work was an LCA of a single dairy feed mill located in Michigan, USA. The primary goal was to conduct a preliminary assessment of dairy feed mill operations and ultimately determine the GHG emissions for 1 kilogram of milled dairy feed.

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Renewable hydrocarbon biofuels are being investigated as possible alternatives to conventional liquid transportation fossil fuels like gasoline, kerosene (aviation fuel), and diesel. A diverse range of biomass feedstocks such as corn stover, sugarcane bagasse, switchgrass, waste wood, and algae, are being evaluated as candidates for pyrolysis and catalytic upgrading to produce drop-in hydrocarbon fuels. This research has developed preliminary life cycle assessments (LCA) for each feedstock-specific pathway and compared the greenhouse gas (GHG) emissions of the hydrocarbon biofuels to current fossil fuels. As a comprehensive study, this analysis attempts to account for all of the GHG emissions associated with each feedstock pathway through the entire life cycle. Emissions from all stages including feedstock production, land use change, pyrolysis, stabilizing the pyrolysis oil for transport and storage, and upgrading the stabilized pyrolysis oil to a hydrocarbon fuel are included. In addition to GHG emissions, the energy requirements and water use have been evaluated over the entire life cycle. The goal of this research is to help understand the relative advantages and disadvantages of the feedstocks and the resultant hydrocarbon biofuels based on three environmental indicators; GHG emissions, energy demand, and water utilization. Results indicate that liquid hydrocarbon biofuels produced through this pyrolysis-based pathway can achieve greenhouse gas emission savings of greater than 50% compared to petroleum fuels, thus potentially qualifying these biofuels under the US EPA RFS2 program. GHG emissions from biofuels ranged from 10.7-74.3 g/MJ from biofuels derived from sugarcane bagasse and wild algae at the extremes of this range, respectively. The cumulative energy demand (CED) shows that energy in every biofuel process is primarily from renewable biomass and the remaining energy demand is mostly from fossil fuels. The CED for biofuel range from 1.25-3.25 MJ/MJ from biofuels derived from sugarcane bagasse to wild algae respectively, while the other feedstock-derived biofuels are around 2 MJ/MJ. Water utilization is primarily from cooling water use during the pyrolysis stage if irrigation is not used during the feedstock production stage. Water use ranges from 1.7 - 17.2 gallons of water per kg of biofuel from sugarcane bagasse to open pond algae, respectively.

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This thesis is composed of three life-cycle analysis (LCA) studies of manufacturing to determine cumulative energy demand (CED) and greenhouse gas emissions (GHG). The methods proposed could reduce the environmental impact by reducing the CED in three manufacturing processes. First, industrial symbiosis is proposed and a LCA is performed on both conventional 1 GW-scaled hydrogenated amorphous silicon (a-Si:H)-based single junction and a-Si:H/microcrystalline-Si:H tandem cell solar PV manufacturing plants and such plants coupled to silane recycling plants. Using a recycling process that results in a silane loss of only 17 versus 85 percent, this results in a CED savings of 81,700 GJ and 290,000 GJ per year for single and tandem junction plants, respectively. This recycling process reduces the cost of raw silane by 68 percent, or approximately $22.6 and $79 million per year for a single and tandem 1 GW PV production facility, respectively. The results show environmental benefits of silane recycling centered around a-Si:H-based PV manufacturing plants. Second, an open-source self-replicating rapid prototype or 3-D printer, the RepRap, has the potential to reduce the environmental impact of manufacturing of polymer-based products, using distributed manufacturing paradigm, which is further minimized by the use of PV and improvements in PV manufacturing. Using 3-D printers for manufacturing provides the ability to ultra-customize products and to change fill composition, which increases material efficiency. An LCA was performed on three polymer-based products to determine the CED and GHG from conventional large-scale production and are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA study indicate that the CED of manufacturing polymer products can possibly be reduced using distributed manufacturing with existing 3-D printers under 89% fill and reduced even further with a solar photovoltaic system. The results indicate that the ability of RepRaps to vary fill has the potential to diminish environmental impact on many products. Third, one additional way to improve the environmental performance of this distributed manufacturing system is to create the polymer filament feedstock for 3-D printers using post-consumer plastic bottles. An LCA was performed on the recycling of high density polyethylene (HDPE) using the RecycleBot. The results of the LCA showed that distributed recycling has a lower CED than the best-case scenario used for centralized recycling. If this process is applied to the HDPE currently recycled in the U.S., more than 100 million MJ of energy could be conserved per annum along with significant reductions in GHG. This presents a novel path to a future of distributed manufacturing suited for both the developed and developing world with reduced environmental impact. From improving manufacturing in the photovoltaic industry with the use of recycling to recycling and manufacturing plastic products within our own homes, each step reduces the impact on the environment. The three coupled projects presented here show a clear potential to reduce the environmental impact of manufacturing and other processes by implementing complimenting systems, which have environmental benefits of their own in order to achieve a compounding effect of reduced CED and GHG.

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Biofuels are an increasingly important component of worldwide energy supply. This research aims to understand the pathways and impacts of biofuels production, and to improve these processes to make them more efficient. In Chapter 2, a life cycle assessment (LCA) is presented for cellulosic ethanol production from five potential feedstocks of regional importance to the upper Midwest - hybrid poplar, hybrid willow, switchgrass, diverse prairie grasses, and logging residues - according to the requirements of Renewable Fuel Standard (RFS). Direct land use change emissions are included for the conversion of abandoned agricultural land to feedstock production, and computer models of the conversion process are used in order to determine the effect of varying biomass composition on overall life cycle impacts. All scenarios analyzed here result in greater than 60% reduction in greenhouse gas emissions relative to petroleum gasoline. Land use change effects were found to contribute significantly to the overall emissions for the first 20 years after plantation establishment. Chapter 3 is an investigation of the effects of biomass mixtures on overall sugar recovery from the combined processes of dilute acid pretreatment and enzymatic hydrolysis. Biomass mixtures studied were aspen, a hardwood species well suited to biochemical processing; balsam, a high-lignin softwood species, and switchgrass, an herbaceous energy crop with high ash content. A matrix of three different dilute acid pretreatment severities and three different enzyme loading levels was used to characterize interactions between pretreatment and enzymatic hydrolysis. Maximum glucose yield for any species was 70% oftheoretical for switchgrass, and maximum xylose yield was 99.7% of theoretical for aspen. Supplemental β-glucosidase increased glucose yield from enzymatic hydrolysis by an average of 15%, and total sugar recoveries for mixtures could be predicted to within 4% by linear interpolation of the pure species results. Chapter 4 is an evaluation of the potential for producing Trichoderma reesei cellulose hydrolases in the Kluyveromyces lactis yeast expression system. The exoglucanases Cel6A and Cel7A, and the endoglucanase Cel7B were inserted separately into the K. lactis and the enzymes were analyzed for activity on various substrates. Recombinant Cel7B was found to be active on carboxymethyl cellulose and Avicel powdered cellulose substrates. Recombinant Cel6A was also found to be active on Avicel. Recombinant Cel7A was produced, but no enzymatic activity was detected on any substrate. Chapter 5 presents a new method for enzyme improvement studies using enzyme co-expression and yeast growth rate measurements as a potential high-throughput expression and screening system in K. lactis yeast. Two different K. lactis strains were evaluated for their usefulness in growth screening studies, one wild-type strain and one strain which has had the main galactose metabolic pathway disabled. Sequential transformation and co-expression of the exoglucanase Cel6A and endoglucanase Cel7B was performed, and improved hydrolysis rates on Avicel were detectable in the cell culture supernatant. Future work should focus on hydrolysis of natural substrates, developing the growth screening method, and utilizing the K. lactis expression system for directed evolution of enzymes.