Sustainable Energy Production in the United States: Life Cycle Assessment of Biofuels and Bioenergy

The United States of America is making great efforts to transform the renewable and abundant biomass resources into cost-competitive, high-performance biofuels, bioproducts, and biopower. This is the key to increase domestic production of transportation fuels and renewable energy, and reduce greenhouse gas and other pollutant emissions. This dissertation focuses specifically on assessing the life cycle environmental impacts of biofuels and bioenergy produced from renewable feedstocks, such as lignocellulosic biomass, renewable oils and fats. The first part of the dissertation presents the life cycle greenhouse gas (GHG) emissions and energy demands of renewable diesel (RD) and hydroprocessed jet fuels (HRJ). The feedstocks include soybean, camelina, field pennycress, jatropha, algae, tallow and etc. Results show that RD and HRJ produced from these feedstocks reduce GHG emissions by over 50% compared to comparably performing petroleum fuels. Fossil energy requirements are also significantly reduced. The second part of this dissertation discusses the life cycle GHG emissions, energy demands and other environmental aspects of pyrolysis oil as well as pyrolysis oil derived biofuels and bioenergy. The feedstocks include waste materials such as sawmill residues, logging residues, sugarcane bagasse and corn stover, and short rotation forestry feedstocks such as hybrid poplar and willow. These LCA results show that as much as 98% GHG emission savings is possible relative to a petroleum heavy fuel oil. Life cycle GHG savings of 77 to 99% were estimated for power generation from pyrolysis oil combustion relative to fossil fuels combustion for electricity, depending on the biomass feedstock and combustion technologies used. Transportation fuels hydroprocessed from pyrolysis oil show over 60% of GHG reductions compared to petroleum gasoline and diesel. The energy required to produce pyrolysis oil and pyrolysis oil derived biofuels and bioelectricity are mainly from renewable biomass, as opposed to fossil energy. Other environmental benefits include human health, ecosystem quality and fossil resources. The third part of the dissertation addresses the direct land use change (dLUC) impact of forest based biofuels and bioenergy. An intensive harvest of aspen in Michigan is investigated to understand the GHG mitigation with biofuels and bioenergy production. The study shows that the intensive harvest of aspen in MI compared to business as usual (BAU) harvesting can produce 18.5 billion gallons of ethanol to blend with gasoline for the transport sector over the next 250 years, or 32.2 billion gallons of bio-oil by the fast pyrolysis process, which can be combusted to generate electricity or upgraded to gasoline and diesel. Intensive harvesting of these forests can result in carbon loss initially in the aspen forest, but eventually accumulates more carbon in the ecosystem, which translates to a CO2 credit from the dLUC impact. Time required for the forest-based biofuels to reach carbon neutrality is approximately 60 years. The last part of the dissertation describes the use of depolymerization model as a tool to understand the kinetic behavior of hemicellulose hydrolysis under dilute acid conditions. Experiments are carried out to measure the concentrations of xylose and xylooligomers during dilute acid hydrolysis of aspen. The experiment data are used to fine tune the parameters of the depolymerization model. The results show that the depolymerization model successfully predicts the xylose monomer profile in the reaction, however, it overestimates the concentrations of xylooligomers.

LIFE CYCLE ASSESSMENTS (LCAs) OF PYROLYSIS-BASED GASOLINE AND DIESEL FROM DIFFERENT REGIONAL FEEDSTOCKS: CORN STOVER, SWITCHGRASS, SUGAR CANE BAGASSE, WASTE WOOD, GUINEA GRASS, ALGAE, AND ALBIZIA

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.

U.S. utilities' experiences with the implementation of energy efficiency programs

In the U.S., many electric utility companies are offering demand-side management (DSM) programs to their customers as ways to save money and energy. However, it is challenging to compare these programs between utility companies throughout the U.S. because of the variability of state energy policies. For example, some states in the U.S. have deregulated electricity markets and others do not. In addition, utility companies within a state differ depending on ownership and size. This study examines 12 utilities’ experiences with DSM programs and compares the programs’ annual energy savings results that the selected utilities reported to the Energy Information Administration (EIA). The 2009 EIA data suggests that DSM program effectiveness is not significantly affected by electricity market deregulation or utility ownership. However, DSM programs seem to generally be more effective when administered by utilities located in states with energy savings requirements and DSM program mandates.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.