Browsing by Author "Reardon, Kenneth F., committee member"
Now showing 1 - 10 of 10
Results Per Page
Sort Options
Item Open Access A techno-economic study on the waste heat recovery options for wet cooled natural gas combined cycle power plants(Colorado State University. Libraries, 2018) Paudel, Achyut, author; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Reardon, Kenneth F., committee memberIncreasing ambient temperature is known to have negative impacts on the performance of gas turbine and combined cycle power plants. There have been multiple approaches to mitigate this performance reduction. One such method involves cooling of the gas turbine inlet air. There are several different commercial techniques available, but they are energy intensive and require large capital investments. One potential option for cost reduction is to recover the waste heat emanating from the power plants to operate thermally activated cooling systems to cool the turbine inlet air. In this study, a 565 MW natural gas combined cycle power plant subjected to different waste heat recovery scenarios and gas turbine inlet chilling is assessed. A simplified thermodynamic and heat transfer model is developed to predict the performance of an evaporatively cooled NGCC power plant at varying ambient conditions. By taking typical meteorological year (TMY3) hourly weather data for two different locations – Los Angeles, California and Houston, Texas – the yearly output for this plant is predicted at a 100% capacity factor. The feasibilities of different waste heat recovery (WHR) systems including a gas turbine exhaust driven absorption chiller, a flue gas driven absorption chiller, a steam driven absorption chiller, and an electrically driven vapor compression chiller are assessed by calculating the Levelized Cost of Electricity (LCOE) for each scenario. In each of these cases, a parametric analysis was performed on the COP and the costs ($ per kWth) of the system. In these cases, the COP was varied from 0.2 to 2.0 (increments of 0.2), whereas the costs were varied logarithmically from $10 to $10,000 per kWth. The results of the analysis showed that for a fixed WHR system cost (i.e., $ per kWth), the system powered by flue gas generated the lowest LCOE, followed by the electrically-driven vapor compression chiller, steam-heated chiller, and finally, the gas turbine exhaust driven chiller for both geographic locations at all COP combinations. The analysis also investigated the impact of fixed investment cost, and the flue gas system again yielded the smallest LCOE and yielded a lower LCOE than the baseline case (no WHR) over a wide range of COPs. The maximum costs each of these systems could tolerate before the LCOE is higher than the baseline case was also determined. The flue gas driven absorption system had the highest tolerable costs at all COP combinations, followed by the vapor compression, steam, and gas turbine exhaust driven systems. As such, the flue gas powered system was identified as the most economic system to reduce the LCOE from the baseline case for a wide range of COP combinations at high tolerable costs for these two locations.Item Open Access Analysis of the relationship between genomic instability, heterozygosity levels and phenotype in Saccharomyces cerevisiae(Colorado State University. Libraries, 2018) Sampaio, Nadia Maria Vieira, author; Argueso, Juan Lucas, advisor; Stargell, Laurie A., committee member; McKay, John K., committee member; Reardon, Kenneth F., committee memberUnderstanding the forces that mediate genome evolution is a central problem in genetics, with implications for diverse processes that range from speciation, to biotechnological applications, to human disease. The central theme of my dissertation was the characterization of two forces, genomic instability and natural selection, that significantly impact genome structure by influencing the levels of genomic heterozygosity. While genomic instability processes can act to erode heterozygosity from the genome, natural selection may favor the maintenance of heterozygous alleles in cases where there is a positive correlation between heterozygosity and higher fitness. In Chapter I, I reviewed different types of mitotic mutations that can result in the appearance of tracts of homozygosity in genomes and recent discoveries about the temporal accumulation of such events. I also introduce the concept of heterosis, a phenomenon characterized by a positive correlation between genomic heterozygosity and phenotype in many species, and its potential role in contributing to the long-term maintenance of genomic heterozygosity. In Chapter II, I describe the characterization of a mechanism of systemic genomic instability in yeast that challenges the conventional model of gradual and independent accumulation of mutations. We showed that a subset of mitotic cells within a population experience bursts of genomic instability, which results in multiple independent events of loss-of-heterozygosity (LOH) accumulating over one or a few generations of mitotic cell division. We named this outcome "systemic genomic instability". The occurrence of this phenomenon was initially identified in the heterozygous yeast strain JAY270, and then validated in a conventional laboratory strain background, whose genome is almost fully homozygous. Elevated rates of coincident LOH was also observed in mutant strains incapable of entering meiosis, indicating cryptic initiation of meiotic recombination followed by return-to-growth in a few cells in the population was not responsible for the higher than expected rates of coincident LOH. This finding brings to light a novel and intriguing mechanism of genomic instability in yeast that has relevant parallels to bursts of accumulation of copy number alterations in the human genome, providing a powerful experimental model system to dissect the fundamental mechanisms responsible for the generation of rapid changes in chromosome structure. In Chapter III, we explored the role that genomic heterozygosity plays on the superior industrial traits of the JAY270 strain. In the previous Chapter we showed that mitotic recombination leading to LOH occurs at a high frequency during JAY270's clonal propagation. These LOH events act against the long-term maintenance of genomic heterozygosity, yet about 60% of JAY270's genome has remained heterozygous over time. We hypothesized that specific heterozygous alleles may have a positive impact on the traits of this strain and therefore were maintained through selection. We generated a collection of inbred strains derived from JAY270, and assessed them phenotypically under different growth conditions. Our results demonstrated that genomic heterozygosity indeed has a substantial impact on two important industrial traits of this strain – heat stress tolerance and growth kinetics. We identified several genomic regions potentially associated with those traits and conducted experiments to investigate the bulk contributions of heterozygosity blocks in three specific chromosomes. This study revealed candidate regions containing loci that potentially underlie important industrial traits of JAY270 and details on the extent to which heterozygosity may impact JAY270's genome evolution and phenotype. The combined results of these research projects provide important insights about the role of genomic instability mechanisms and their phenotypic outcomes in determining genome evolution, contributing discoveries that may have important practical implications for diverse fields, including biotechnology, cancer development and evolution, as well as genome sciences.Item Open Access Assay development for pathogen detection at the point-of-need(Colorado State University. Libraries, 2020) Carrell, Cody S., author; Henry, Charles S., advisor; Farmer, Delphine K., committee member; McNally, Andrew, committee member; Reardon, Kenneth F., committee memberInfectious diseases are responsible for roughly one third of worldwide deaths, which disproportionately occur in low- and middle-income countries. Government health agencies recognize high quality diagnostics as a key tool to slow the spread and reduce the burden of disease in these countries. The same diagnostics that have minimized deaths from infectious disease in developed nations, however, cannot simply be implemented in all locations. Low- and middle-income countries lack the financial resources and infrastructure required to use the sophisticated instruments found in modern hospital laboratories. Instead of relying on current diagnostic technologies to reduce the burden of infectious disease, there is an urgent need to develop new technologies suited for the resource-limited settings they will be used in. The work described in this thesis aims to advance the capabilities of diagnostic sensors for use at the point-of-need. Microfluidic devices have been used for decades to perform complex analysis using compact devices with small sample and reagent volumes. Their portability and low-cost make them ideal candidates for analysis in resource limited settings, but their fabrication is tedious and expensive. To improve the fabrication process, Chapter Two of this thesis describes two methods for simplified 3D-printing of microfluidic devices. The 3D printer and resin used are inexpensive and commercially available and the fabrication process is not limited by the need to remove uncured resin from enclosed channels. Instead, open-faced channels in 3D-printed pieces were silanized and sealed to a secondary substrate. Common microfluidic devices including a droplet generator and herringbone mixer were created with the new fabrication method to demonstrate the strength of the seal and ability for the printer to create microfluidic channels. We envision this method being used for rapid prototyping and increased innovation in the field of microfluidic sensors. Traditional polymer microfluidics are limited in their usefulness in point-of-need situations because they require a pump to drive flow. Paper-based microfluidics use capillary action to drive flow instead of a pump and have emerged as an easy-to-use and inexpensive alternative to traditional microfluidics in situations where a power source is not available. However, paper-based microfluidics often suffer from poor analytical performance, and efforts to improve result in increased complexity. Chapter Three of this thesis describes a paper-based device that increases the sensitivity of a Salmonella assay while retaining ease-of-use. The device combines paper-pads for reagent storage with a 3D-printed rotational manifold to perform an enzyme-linked immunosorbent assay (ELISA). Typically, this assay requires dozens of complex pipetting steps, but the rotary device simplifies this process into four semi-automated steps. A detection limit of 440 colony forming units/mL was found using the paper-based device. As demonstrated in Chapter Three, common issues with paper-based microfluidics can be solved by integrating paper with other inexpensive components like 3D-printed polymer. In the final study in Chapter Four, we created a device to further simplify the steps of an ELISA using a combination of paper, polyester transparency film, and double-sided adhesive. The device, termed a disposable ELISA (dELISA), automatically performed the sequential reagent delivery and washing steps required for a traditional ELISA and require only two end user steps. The dELISA was then used to perform a serology assay for SARS-CoV-2 antibodies from whole-blood. The detection limit of the assay was 2.8 ng/mL for the dELISA, which was nearly identical to the detection limit found using a tradition well-plate assay (1.2 ng/mL).Item Open Access Characterizing biological systems: quantitative methods for synthetic genetic circuits in plants and intracellular mechanics(Colorado State University. Libraries, 2018) Xu, Wenlong, author; Prasad, Ashok, advisor; Medford, June I., committee member; Reardon, Kenneth F., committee member; Munsky, Brian E., committee memberTo view the abstract, please see the full text of the document.Item Open Access Determining the effect of primer mismatches on quantitative PCR accuracy and developing guidance for design of primers with sequence variations(Colorado State University. Libraries, 2012) Ledeker, Brett Michael, author; De Long, Susan K., advisor; Omur-Ozbek, Pinar, committee member; Reardon, Kenneth F., committee memberAlthough quantitative PCR (qPCR) is a powerful tool for investigating environmental systems, target gene sequences for organisms of interest often are not well known, which has resulted in few reliable primers for many applications. Additionally, the sequences of target genes found in diverse strains often contain sequence variations, and therefore, primer sets containing single or multiple primer-template mismatches are common. However, the detrimental impact of these mismatches on quantification accuracy and amplification efficiency has not been investigated thoroughly. Thus, the research objectives of this study were to elucidate the relationships between primer mismatches and the accuracy of qPCR assays and to develop guidance for designing primers targeting genes displaying sequence variations. The pcrA gene (encoding perchlorate reductase) from Dechloromonas agitata was used as a model system for this study, and a linearized plasmid containing the cloned pcrA gene was used as the qPCR template. A large number of pcrA primers (16 forward and 16 reverse) were designed containing from zero to three mismatches at various locations. Combinations of primers were tested to determine the impact of mismatches on the amplification efficiency, the threshold cycle (CT), and the quantification accuracy. Quantification accuracy was calculated as the percent detected by dividing the quantity measured with mismatch primers by the quantity measured with perfect match primers and multiplying by 100. Single mismatches at the 3' end resulted in quantification accuracies as low as ~3%, and single mismatches at the 5' end resulted in quantification accuracies as low as ~33%. Double and triple mismatches at the 5' resulted in quantification accuracies as low as ~17% and ~2%, respectively. Reductions in quantification accuracy correlated with increases in CT induced by mismatches but not with changes in amplification efficiency. Combining mismatched forward and reverse primers had an impact equivalent to the combined effect of the individual mismatch primers. Analogous qPCR tests were run with three other model genes: celS (encoding family 48 cellulase), C23O (encoding catechol dioxygenase, involved in toluene degradation), and hydA (encoding periplasmic hydrogenase, involved in fermentation). Primers were artificially designed to contain mismatches with these target genes, and results demonstrated that single or double mismatches can have a substantial detrimental impact on quantification accuracy in a broad range of systems. The results of this study indicate that caution must be taken to avoid mismatches when designing qPCR primers targeting genes with sequence variations and the findings serve to guide future design of primers for accurately quantifying genes in environmentally relevant systems.Item Open Access Engineering system modeling for sustainability assessment(Colorado State University. Libraries, 2016) Barlow, Jay, author; Quinn, Jason C., advisor; Willson, Bryan, committee member; Reardon, Kenneth F., committee memberThe increase in global greenhouse gas emissions has driven interest in the development of renewable energy sources. The commercial development of emerging renewable technologies like algal biofuels requires the identification of an economically viable production pathway. This study examined the sustainability of generating renewable diesel via hydrothermal liquefaction (HTL) of algal biomass from an attached growth architecture. Pilot-scale growth studies and laboratory-scale HTL experiments validated an engineering system model, which facilitated analysis of economic feasibility and environmental impact of the system at full scale. Techno-economic analysis (TEA) results indicate an optimized minimum fuel selling price (MFSP) of $11.90 gal-1, and life-cycle assessment (LCA) found a global warming potential (GWP) of -44 g CO2-e MJ-1 and net energy ratio of 0.33. Results from this work identified current gaps in sustainability assessment through TEA and LCA. Two needs were identified to improve sustainability assessment: the internalization of a carbon emission price into TEA and the consideration of the time-value of carbon emissions in LCA. With these effects considered, MFSP and GWP increase by 23% for the modeled biofuels system. Results from a harmonized model of an array of energy technologies indicate that prices for fossil-based energy increase 200% and GWP increases 25% when these factors are considered, whereas low-emitting technologies increase minimally in both metrics. Based on these findings, the development of improved sustainability assessment methodology is proposed.Item Open Access Investigation of vertical mixing in raceway pond systems using computational fluid dynamics(Colorado State University. Libraries, 2021) Shen, Chen, author; Dandy, David S., advisor; Reardon, Kenneth F., committee member; Bradley, Thomas, committee member; Prasad, Ashok, committee memberRaceway ponds are widely used as cost-efficient and easily set up outdoor algal cultivation systems. Growth rates strongly depend on cumulative light exposure, which can be predicted using accurate computational fluid dynamics simulations of the ponds' dynamics. Of particular importance in computing the three-dimensional velocity field is the vertical component that is responsible for transporting cells between light and dark regions. Numerous previous studies utilized one of the turbulence models derived from the Reynolds-averaged Navier–Stokes equations to predict the turbulent behaviors in raceway ponds. Because vertical fluid motion is secondary and the primary flow is in the horizontal plane, using one of the Reynolds-averaged Navier–Stokes turbulence equations has the potential to decrease the fidelity of information about vertical motion. In Chapter 2, large eddy simulation (LES) and k-ɛ models are used to simulate fluid dynamics in a mesoscale (615 L) raceway pond system and compared with laboratory data. It is found that swirling motions present in the liquid phase play an essential role in the vertical mixing performance. LES is shown to have the capability to provide more realistic and highly time dependent hydrodynamic predictions when compared with experimental data, while the k-ε model under-predicts the magnitude of the swirling behavior and over-predicts the volume of dead zones in the pond. The instantaneous spatial distribution of high vertical velocity regions and dead zones, as well as their time-accumulated volume fraction, are investigated. LES results suggest that swirling motion exists in the low-velocity regions predicted by the k-ɛ model to be dead zones where the high-velocity flow takes place over more than 50% of the flow time, and the recirculating motion may be responsible for stratification and unwanted chemical accumulation. LES results indicate that strong vortex regions exist near the paddle wheel, and the first 180°bend, and the geometry of the divider will contribute to the generation of vortices, enhance the vertical motion, and increase the light/dark effect. In Chapter 2, it will be demonstrated that the swirling motion appears to play a critical role in enhancing the vertical mixing and enhancing the light/dark effect. In Chapter 3, a dimensional analysis is performed to predict the persistence of the swirling motion generated at the hairpin bend by modeling 7 raceway pond geometries with shape ratios—defined as the ratio of the width of a straight section to the liquid depth—ranging from 0.5 to 7.05, and Dean numbers ranging from 16,140 to 242,120. The fluid dynamics were simulated using a transient multiphase solver with a large eddy simulation turbulence model in the open-source code open Foam framework. The results demonstrate that the number of instances of swirling motion strongly depends on the shape ratio of the ponds. When the shape ratio is close to 1, a single instance of swirling motion is most likely to be found downstream of the first 180° bend, while multiple occurrences of swirling motion are observed when the shape ratio is larger than 1. It was also found that the strength of the swirling motion has a linear dependence on the average velocity magnitude downstream of the first 180° bend after the paddle wheel. The strength and persistence of the swirling motion are fit with a rational function that can be used to predict the mixing performance of a raceway pond without the need for complicated and expensive simulations. In Chapter 4, transient particle tracking is performed to predict microalgae cells' vertical motion for more than 800 s, which is subsequently converted to the cells' light intensity history. The data of light intensity history, along with the velocity field, are compared to validate the hypothesis that the cells' trajectories and L/D transition are significantly dominated by vertical mixing in raceway ponds, mostly, the swirling motions generated by the secondary flow in the hairpin bends. It is found that the region where cells have a high probability to experience light/dark transitions coincides with the spatial prediction of swirling motion, suggesting that the swirling motion significantly contributes to reducing the light/dark frequency exposure by microalgae. In Chapter 5, a novel use of vortex generators in a raceway pond is presented that passively generate swirling motion in the regions where the strength of vertical motion is predicted to otherwise be low. The flow field is quantitatively simulated using computational fluid dynamics using the large eddy simulation turbulence model. Persistence lengths of the swirling motion generated by the vortex generators indicate that significant vertical mixing can be achieved by placing vortex generators in the straight section opposite the paddle wheel, downstream of the first hairpin bend. Relatively simple vortex generators are capable of creating stronger swirling motions that persist for a longer distance than those caused by the paddle wheel. For optimal performance, vortex generators are positioned side by side but in opposite directions, and their diameters should be equal to or slightly less than the liquid depth. The optimal length of a 0.18 m diameter vortex generator in a 0.2 m deep pond was determined to be 0.3 m. Furthermore, it has been demonstrated that a longer persistence length is achieved by inducing a swirling motion with its rotational axis parallel to the primary flow direction.Item Open Access Metabolic engineering of cyanobacteria: developing molecular tools and characterizing strain performance in light:dark cycles(Colorado State University. Libraries, 2015) Cheah, Yi Ern, author; Peebles, Christie M., advisor; Reardon, Kenneth F., committee member; Prasad, Ashok, committee member; Peers, Graham, committee memberThe conversion of CO2 and light energy to biofuels holds promise for a renewable and environmentally responsible source of energy that could meet the growing demand for transportation fuels. However, early efforts to commercialize biofuels from plants were hampered by social, economic, and technological difficulties. Photosynthetic microbes present an opportunity for a more efficient conversion of fixed carbon to biofuels by bypassing the need of harvesting sugars from plants to be fermented by heterotrophic bacteria. More recently, cyanobacterial technologies have received considerable interest due to their ease of genetic manipulation that enables them to produce a myriad of biofuels and biochemicals directly from CO2. This relatively nascent technology needs to be developed in order to realize its commercial potential. Metabolic engineering is the systematic improvement of strains through the use of a variety of theoretical and experimental techniques. To date, heterologous pathways expression has been the most successful in model heterotrophic organisms (e.g. E. coli) and advances from these systems have to be carefully transferred over to cyanobacteria. Though several studies have demonstrated the capability of engineering cyanobacteria to produce biofuels, there is yet to be any commercially feasible production platform of fuels from CO2. Amongst the challenges is the need to improve yields and titers from recombinant strains. However, the physiology of cyanobacteria is distinct from that of heterotrophic organisms and therefore requires careful design and study in order to optimize for higher yields. This thesis contributes several technologies to foster the scale-up of cyanobacteria systems from the bench to industrial scale. We first developed a markerless chromosomal modification method in WT Synechocystis PCC6803 that could reduce the metabolic load and cultivation cost compared to plasmid-based expression methods. We established a counter-selection method that necessitates two rounds of modifications in order to screen for the desired mutant harboring the gene(s) of interest. In the first round, a synthetic circuit consisting of a nickel inducible toxin gene (mazF) and a kanamycin resistance marker is integrated into a specific locus in WT Synechocystis. In the second round, a construct harboring gene(s) of interest is transformed into the prerequisite strains and screen on Ni2+ to obtain the desired mutants. Next we established a free fatty acid (FFA) producing platform in Synechocystis PCC6803 by pursuing three goals: 1) deletion of acyl-acyl carrier protein (acyl-ACP) synthetase (aas), 2) optimize the expression of thioesterase I (TesA) with a promoter library and 3) examine the effects of light:dark cycles on FFA production in Synechocystis. For the first goal, we were successful in engineering an aas deletion strain that had increased FFA production. In the second goal, we developed four Synechocystis variants with increasing TesA expression strengths from the aas deletion strain. No increase in FFA production was observed between the TesA expressing strains (with aas deleted) compared to the baseline aas deletion strain. On the protein level, we found no evidence of TesA enzyme activity even though TESA peptides were detected in our Synechocystis strains. In the third goal, we learn that diel light:dark cycles causes a significant decrease in production of FFAs in FFA producing mutants of Synechocystis compared to continuous light. We did not observe any transcriptional changes in the fatty acid biosynthesis pathway between our WT and FFA producing strains to explain these changes. In summary, this thesis is impactful in two ways: 1) it entails the development of a markerless genetic modification method for use in cyanobacteria and 2) it characterizes the production of FFAs from engineered cyanobacteria under diel light:dark cycles. Overall, this thesis helps address the difficulties in the development of cyanobacteria systems for eventual use in an industrial setting.Item Open Access Modeling soil organic matter: theory, development, and applications in bioenergy cropping systems(Colorado State University. Libraries, 2015) Campbell, Eleanor Elizabeth, author; Paustian, Keith, advisor; Parton, William J., committee member; Cotrufo, M. Francesca, committee member; Reardon, Kenneth F., committee memberSoil organic matter (SOM) is a complex, dynamic, and highly variable soil constituent that is of fundamental importance to many soil functions, terrestrial ecosystem processes, and biogeochemical cycles. Its importance extends across scales, ranging from site-specific impacts on soil fertility to the global net exchange of carbon between terrestrial systems and the atmosphere. Soil organic matter is impacted by human activities, as seen most directly in agricultural systems. In this context, SOM models play an important role in integrating the understanding of complex, interacting soil processes across temporal and spatial scales, contributing to land use decision making by providing comparative evaluation of soil impacts associated with different management practices. Crop-based bioenergy feedstock productions systems are an emerging area for these types of SOM model applications. However, model evaluations are dependent on the theoretical basis of a given SOM model, as well as the quality of data used to drive the model for a given system or management scenario. This study therefore explores linkages between advances in the theoretical understanding of SOM dynamics, the development of SOM models to reflect these advances, and the application of SOM models to assess crop-based bioenergy production systems. First, five emerging areas in SOM research were reviewed in the context of SOM models, including SOM stabilization mechanisms, saturation kinetics, temperature sensitivity, dynamics in deep soils, and incorporation into earth system models. These reviews demonstrated the importance of identifying where SOM model development and applications are most limited, whether in theoretical understanding, in model implementation, or in data availability. For example, SOM saturation kinetics is theoretically well understood but remains difficult to implement in SOM models, only yielding improvements in a narrow set of ecological conditions. SOM temperature sensitivity and deep soil dynamics, however, are more limited by poor data availability in addition to poor theoretical understanding of interacting processes. A selection of shortfalls in SOM modeling were then addressed and explored with the Litter Decomposition and Leaching (LIDEL) model, a litter decomposition model that incorporates dynamic microbial carbon use efficiency (CUE) and yields dissolved organic carbon (DOC) as one of the byproducts of litter decomposition. In this analysis a hierarchical Bayesian statistical approach was used to test model performance and estimate unknown model parameters using experimental data. While this analysis showed the LIDEL model successfully integrates hypotheses for litter nitrogen and lignin controls on dynamic microbial CUE and the generation of DOC from litter decomposition, there remains a great deal of uncertainty in the rate of microbial biomass turnover as well as the proportioning of biomass from microbial turnover between solid versus soluble microbial products. Targeted experimental evaluation of the generation of DOC from microbes versus litter would support greater certainty in these model parameters and further model development for more general applications. Finally, the performance of the DAYCENT ecosystem model was evaluated in simulating US corn residue removal and Brazilian sugarcane production, two types of crop-based bioenergy feedstocks. DAYCENT is a process-based ecosystem model that integrates a soil organic carbon model to simulate carbon and nitrogen cycling processes through plant-soil interactions. The results of DAYCENT corn residue removal simulations highlighted several DAYCENT model biases, such as low corn yield estimates in dry regions and an overestimation of soil carbon loss with conventional tillage. Despite these biases, the results showed the importance of considering interactive effects between corn residue removal and other crop management practices in this type of bioenergy feedstock production system. The results suggest corn residue removal is ideally paired with management practices—such as reduced tillage—to maintain or improve soil carbon stocks. The analysis of Brazilian sugarcane management practices also highlighted management practices poorly simulated by DAYCENT, in particular identifying the need to improve DAYCENT simulations of high N₂O emission conditions observed in mechanically-harvested sugarcane, perhaps by adding simulation of DOC movement across the soil profile. However, this analysis also identified a need for more accurate and consistent daily precipitation data to drive DAYCENT simulations of N₂O emissions from Brazilian sugarcane management practices, particularly as there is interest in regionally-scaled analyses of direct greenhouse gas emissions from sugarcane production in Brazil. Taken together, the results of this study show the importance of a close connection between emerging areas in SOM theory, SOM model developments, and SOM model applications in crop-based bioenergy feedstock production systems. This connection allows for the identification of specific areas in need of further research, whether developing new modeling approaches or gathering additional data to parameterize, drive, and evaluate model simulations. This connection should remain a central emphasis as SOM models are increasingly incorporated into crop-based bioenergy policy and land management decision making.Item Open Access Physiochemical properties and evaporation dynamics of bioalcohol-gasoline blends(Colorado State University. Libraries, 2018) Abdollahipoor, Bahareh, author; Windom, Bret C., advisor; Reardon, Kenneth F., committee member; Olsen, Daniel B., committee memberAfter fermentation, the concentration of bioethanol is only 8-12 wt%. To produce anhydrous ethanol fuel, a significant amount of energy is required for separation and dehydration. Once the azeotrope composition is reached, distillation can no longer be exploited for purification and other expensive methods must be used. Replacing anhydrous ethanol fuel with hydrous ethanol (at the azeotrope composition) can result in significant energy and cost savings during production. Currently there is a lack of available thermophysical property data for hydrous ethanol gasoline fuel blends. This data is important to understand the effect of water on critical fuel properties and to evaluate the potential of using hydrous ethanol fuels in conventional and optimized spark ignition engines. In this study, the thermophysical properties, volatility behavior, evaporation dynamic, and mixing/sooting potential of various hydrous and anhydrous ethanol blends with gasoline were characterized. Results show that the properties of low and mid-level hydrous ethanol blends are not significantly different from those of anhydrous ethanol blends, suggesting that hydrous ethanol blends have the potential to be used in current internal combustion engines as a drop-in biofuel. Dual-alcohol approach, mixing lower and higher alcohols with gasoline to obtain a blend with a vapor pressure close to that of the base gasoline, is a potential way to circumvent issues with single alcohol blends. In second project, the azeotropic volatility behavior and mixing/sooting potential of dual-alcohol gasoline blends were studied by monitoring the distillation composition evolution and use of droplet evaporation model.