Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

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.

Investigating the effect of construction management strategies on project greenhouse gas emissions using interactive simulation

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.

Approach to carbon dioxide capture and storage at ambient conditions

Carbon dioxide (CO2) capture and storage experiments were conducted at ambient conditions in varying weight % sodium carbonate (Na2CO3) solutions. Experiments were conducted to determine the optimal amount of Na2CO3 in solution for CO2 absorption. It was concluded that a 2% Na2CO3 solution, by weight, was the most efficient solution. The 2% Na2CO3 solution is able to absorb 0.5 g CO2/g Na2CO3. These results led to studies to determine how the gas bubble size affected carbon dioxide absorption in the solution. Studies were conducted using ASTM porosity gas diffusers to vary the bubble size. Gas diffusers with porosities of fine, medium, and extra coarse were used. Results found that the medium porosity gas diffuser was the most efficient at absorbing CO2 at 50%. Variation in the bubble size concluded that absorption of carbon dioxide into the sodium carbonate solution does depend on the bubble size, thus is mass transfer limited. Once the capture stage was optimized (amount of Na2CO3 in solution and bubble size), the next step was to determine if carbon dioxide could be stored as a calcium carbonate mineral using calcium rich industrial waste and if the sodium carbonate solution could be simultaneously regenerated. Studies of CO2 sequestration at ambient conditions have shown that it is possible to permanently sequester CO2 in the form of calcium carbonate using a calcium rich industrial waste. Studies have also shown that it is possible to regenerate a fraction of the sodium carbonate solution.

A Novel Approach to Carbon Dioxide Capture and Storage

The novel approach to carbon capture and storage (CCS) described in this dissertation is a significant departure from the conventional approach to CCS. The novel approach uses a sodium carbonate solution to first capture CO2 from post combustion flue gas streams. The captured CO2 is then reacted with an alkaline industrial waste material, at ambient conditions, to regenerate the carbonate solution and permanently store the CO2 in the form of an added value carbonate mineral. Conventional CCS makes use of a hazardous amine solution for CO2 capture, a costly thermal regeneration stage, and the underground storage of supercritical CO2. The objective of the present dissertation was to examine each individual stage (capture and storage) of the proposed approach to CCS. Study of the capture stage found that a 2% w/w sodium carbonate solution was optimal for CO2 absorption in the present system. The 2% solution yielded the best tradeoff between the CO2 absorption rate and the CO2 absorption capacity of the solutions tested. Examination of CO2 absorption in the presence of flue gas impurities (NOx and SOx) found that carbonate solutions possess a significant advantage over amine solutions, that they could be used for multi-pollutant capture. All the NOx and SOx fed to the carbonate solution was able to be captured. Optimization studies found that it was possible to increase the absorption rate of CO2 into the carbonate solution by adding a surfactant to the solution to chemically alter the gas bubble size. The absorption rate of CO2 was increased by as much as 14%. Three coal combustion fly ash materials were chosen as the alkaline industrial waste materials to study the storage CO2 and regeneration the absorbent. X-ray diffraction analysis on reacted fly ash samples confirmed that the captured CO2 reacts with the fly ash materials to form a carbonate mineral, specifically calcite. Studies found that after a five day reaction time, 75% utilization of the waste material for CO2 storage could be achieved, while regenerating the absorbent. The regenerated absorbent exhibited a nearly identical CO2 absorption capacity and CO2 absorption rate as a fresh Na2CO3 solution.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

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.

NICKEL-COBALT SOLID SOLUTION AND ITS APPLICATIONS AS CATALYSTS FOR CARBON DIOXIDE REFORMING OF METHANE

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.

The effect of demand, tank parameters, and pumping stations on energy use in municipal drinking water distribution systems

Two of the indicators of the UN Millennium Development Goals ensuring environmental sustainability are energy use and per capita carbon dioxide emissions. The increasing urbanization and increasing world population may require increased energy use in order to transport enough safe drinking water to communities. In addition, the increase in water use would result in increased energy consumption, thereby resulting in increased green-house gas emissions that promote global climate change. The study of multiple Municipal Drinking Water Distribution Systems (MDWDSs) that relates various MDWDS aspects--system components and properties--to energy use is strongly desirable. The understanding of the relationship between system aspects and energy use aids in energy-efficient design. In this study, components of a MDWDS, and/or the characteristics associated with the component are termed as MDWDS aspects (hereafter--system aspects). There are many aspects of MDWDSs that affect the energy usage. Three system aspects (1) system-wide water demand, (2) storage tank parameters, and (3) pumping stations were analyzed in this study. The study involved seven MDWDSs to understand the relationship between the above-mentioned system aspects in relation with energy use. A MDWDSs model, EPANET 2.0, was utilized to analyze the seven systems. Six of the systems were real and one was a hypothetical system. The study presented here is unique in its statistical approach using seven municipal water distribution systems. The first system aspect studied was system-wide water demand. The analysis involved analyzing seven systems for the variation of water demand and its impact on energy use. To quantify the effects of water use reduction on energy use in a municipal water distribution system, the seven systems were modeled and the energy usage quantified for various amounts of water conservation. It was found that the effect of water conservation on energy use was linear for all seven systems and that all the average values of all the systems' energy use plotted on the same line with a high R 2 value. From this relationship, it can be ascertained that a 20% reduction in water demand results in approximately a 13% savings in energy use for all seven systems analyzed. This figure might hold true for many similar systems that are dominated by pumping and not gravity driven. The second system aspect analyzed was storage tank(s) parameters. Various tank parameters: (1) tank maximum water levels, (2) tank elevation, and (3) tank diameter were considered in this part of the study. MDWDSs use a significant amount of electrical energy for the pumping of water from low elevations (usually a source) to higher ones (usually storage tanks). The use of electrical energy has an effect on pollution emissions and, therefore, potential global climate change as well. Various values of these tank parameters were modeled on seven MDWDSs of various sizes using a network solver and the energy usage recorded. It was found that when averaged over all seven analyzed systems (1) the reduction of maximum tank water level by 50% results in a 2% energy reduction, (2) energy use for a change in tank elevation is system specific, and (2) a reduction of tank diameter of 50% results in approximately a 7% energy savings. The third system aspect analyzed in this study was pumping station parameters. A pumping station consists of one or more pumps. The seven systems were analyzed to understand the effect of the variation of pump horsepower and the number of booster stations on energy use. It was found that adding booster stations could save energy depending upon the system characteristics. For systems with flat topography, a single main pumping station was found to use less energy. In systems with a higher-elevation neighborhood, however, one or more booster pumps with a reduced main pumping station capacity used less energy. The energy savings for the seven systems was dependent on the number of boosters and ranged from 5% to 66% for the analyzed five systems with higher elevation neighborhoods (S3, S4, S5, S6, and S7). No energy savings was realized for the remaining two flat topography systems, S1, and S2. The present study analyzed and established the relationship between various system aspects and energy use in seven MDWDSs. This aids in estimating the amount of energy savings in MDWDSs. This energy savings would ultimately help reduce Greenhouse gases (GHGs) emissions including per capita CO 2 emissions thereby potentially lowering the global climate change effect. This will in turn contribute to meeting the MDG of ensuring environmental sustainability.

Cold-Start Emissions testing of Snowmobiles Using Ethanol and Gasoline

Increasing prices for fuel with depletion and instability in foreign oil imports has driven the importance for using alternative and renewable fuels. The alternative fuels such as ethanol, methanol, butyl alcohol, and natural gas are of interest to be used to relieve some of the dependence on oil for transportation. The renewable fuel, ethanol which is made from the sugars of corn, has been used widely in fuel for vehicles in the United States because of its unique qualities. As with any renewable fuel, ethanol has many advantages but also has disadvantages. Cold startability of engines is one area of concern when using ethanol blended fuel. This research was focused on the cold startability of snowmobiles at ambient temperatures of 20 °F, 0 °F, and -20 °F. The tests were performed in a modified 48 foot refrigerated trailer which was retrofitted for the purpose of cold-start tests. Pure gasoline (E0) was used as a baseline test. A splash blended ethanol and gasoline mixture (E15, 15% ethanol and 85% gasoline by volume) was then tested and compared to the E0 fuel. Four different types of snowmobiles were used for the testing including a Yamaha FX Nytro RTX four-stroke, Ski-doo MX Z TNT 600 E-TEC direct injected two stroke, Polaris 800 Rush semi-direct injected two-stroke, and an Arctic Cat F570 carbureted two-stroke. All of the snowmobiles operate on open loop systems which means there was no compensation for the change in fuel properties. Emissions were sampled using a Sensors Inc. Semtech DS five gas emissions analyzer and engine data was recoded using AIM Racing Data Power EVO3 Pro and EVO4 systems. The recorded raw exhaust emissions included carbon monoxide (CO), carbon dioxide (CO2), total hydrocarbons (THC), and oxygen (O2). To help explain the trends in the emissions data, engine parameters were also recorded. The EVO equipment was installed on each vehicle to record the following parameters: engine speed, exhaust gas temperature, head temperature, coolant temperature, and test cell air temperature. At least three consistent tests to ensure repeatability were taken at each fuel and temperature combination so a total of 18 valid tests were taken on each snowmobile. The snowmobiles were run at operating temperature to clear any excess fuel in the engine crankcase before each cold-start test. The trends from switching from E0 to E15 were different for each snowmobile as they all employ different engine technologies. The Yamaha snowmobile (four-stroke EFI) achieved higher levels of CO2 with lower CO and THC emissions on E15. Engine speeds were fairly consistent between fuels but the average engine speeds were increased as the temperatures decreased. The average exhaust gas temperature increased from 1.3-1.8% for the E15 compared to E0 due to enleanment. For the Ski-doo snowmobile (direct injected two-stroke) only slight differences were noted when switching from E0 to E15. This could possibly be due to the lean of stoichiometric operation of the engine at idle. The CO2 emissions decreased slightly at 20 °F and 0 °F for E15 fuel with a small difference at -20 °F. Almost no change in CO or THC emissions was noted for all temperatures. The only significant difference in the engine data observed was the exhaust gas temperature which decreased with E15. The Polaris snowmobile (semi-direct injected two-stroke) had similar raw exhaust emissions for each of the two fuels. This was probably due to changing a resistor when using E15 which changed the fuel map for an ethanol mixture (E10 vs. E0). This snowmobile operates at a rich condition which caused the engine to emit higher values of CO than CO2 along with exceeding the THC analyzer range at idle. The engine parameters and emissions did not increase or decrease significantly with decreasing temperature. The average idle engine speed did increase as the ambient temperature decreased. The Arctic Cat snowmobile (carbureted two-stroke) was equipped with a choke lever to assist cold-starts. The choke was operated in the same manor for both fuels. Lower levels of CO emissions with E15 fuel were observed yet the THC emissions exceeded the analyzer range. The engine had a slightly lower speed with E15.

Nitrogen removal and sustainability of vertical flow constructed wetlands for small scale wastewater treatment

The challenge for wastewater professionals is to design and operate treatment processes that support human well being and are environmentally sensitive throughout the life-cycle. This research focuses on one technology for small-scale wastewater treatment: the vertical flow constructed wetland (VFCW), which is herein investigated for the capacity to remove ammonium and nitrate nitrogen from wastewater. Hydraulic regime and presence/absence of vegetation are the basis for a three-phase bench scale experiment to determine oxygen transfer and nitrogen fate in VFCWs. Results show that 90% NH4+-N removal is achieved in aerobic downflow columns, 60% NO3--N removal occurs in anaerobic upflow columns, and 60% removal of total nitrogen can be achieved in downflow-upflow in-series. The experimental results are studied further using a variably saturated flow and reactive transport model, which allows a mechanistic explanation of the fate and transport of oxygen and nitrogen. The model clarifies the mechanisms of oxygen transport and nitrogen consumption, and clarifies the need for readily biodegradable COD for denitrification. A VFCW is then compared to a horizontal flow constructed wetland (HFCW) for life cycle environmental impacts. High areal emissions of greenhouse gases from VFCWs compared to HFCWs are the driver for the study. The assessment shows that because a VFCW is only 25% of the volume of an HFCW designed for the same treatment quality, the VFCW has only 25-30% of HFCW impacts over 12 impact categories and 3 damage categories. Results show that impacts could be reduced by design improvements. Design recommendations are downflow wetlands for nitrification, upflow wetlands for denitrification, series wetlands for total nitrogen removal, hydraulic load of 142 L/m2d, 30 cm downflow wetland depth, 1.0 m upflow wetland depth, recycle, vegetation and medium-grained sand. These improvements will optimize nitrogen removal, minimize gaseous emissions, and reduce wetland material requirements, thus reducing environmental impact without sacrificing wastewater treatment quality.

Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

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.

Kinetic characterization for pretreatment of timber varieties and switchgrass using diluted acid hydrolysis

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.

Life cycle assessment of biofuels produced by the new integrated hydropyrolysis-hydroconversion (IH2) process

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.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

BEYOND ROOTS ALONE: NOVEL METHODOLOGIES FOR ANALYZING COMPLEX SOIL AND MINIRHIZOTRON IMAGERY USING IMAGE PROCESSING AND GIS TOOLS

Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.