University of Florida's Stan Mayfield Demonstration Biorefinery DatasetThe University of Florida's Stan Mayfield Demonstration Biorefinery enabled the study of the most effective ways to convert sugarcane and sorghum agricultural residues into cellulosic ethanol. This dataset provides details on 23 campaigns run at the biorefinery between 2012 and 2016. The data were published using GitHub, allowing interested users to browse the documentation, download specific files, download the entire dataset.
This workshop examines the potential benefits, feasibility, and barriers to the use of biofuels in place of heavy fuel oil (HFO) and marine gas oil for marine vessels. More than 90% of world’s shipped goods
travel by marine cargo vessels powered by internal combustion (diesel) engines using primarily low-cost residual HFO, which is high in sulfur content. Recognizing that marine shipping is the largest source of
anthropogenic sulfur emissions and is a significant source of other pollutants including particulates, nitrogen oxides, and carbon dioxide (CO2), the International Maritime Organization enacted regulations to
lower the fuel sulfur content from 3.5 wt.% to 0.5 wt.% in 2020. These regulations require ship operators either to use higher-cost, low-sulfur HFO or to seek other alternatives for reducing sulfur emissions (i.e.,
scrubbers, natural gas, distillates, and/or biofuels). The near-term options for shipowners to comply with regulations include fueling with low-sulfur HFO or distillate fuels or installing emissions control systems.
However, few refineries are equipped to produce low-sulfur HFO. Likewise, the current production rates of distillates do not allow the necessary expansion required to fuel the world fleet of shipping vessels
(which consume around 330 million metric tons). This quantity is more than twice that used in the United States for cars and trucks. The other near-term option is to install emission control systems, which also
requires a significant investment. All of these options significantly increase operational costs. Because of such costs, biofuels have become an attractive alternative since they are inherently low in sulfur and
potentially also offer greenhouse gas benefits. Based on this preliminary assessment, replacing HFO in large marine vessels with minimally processed, heavy biofuels appears to have potential as a path to
reduced emissions of sulfur, CO2, and criteria emissions. Realizing this opportunity will require deeper knowledge of (1) the combustion characteristics of biofuels in marine applications, (2) their compatibility
for blending with conventional marine fuels (including HFO), (3) needs and costs for scaling up production and use, and (4) a systems assessment of their life cycle environmental impacts and costs. It is
recommended that a research program investigating each of these aspects be undertaken to better assess the efficacy of biofuels for marine use.
The 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy is the third in a series of national biomass resource assessments commissioned by the U.S. Department of Energy. This report aims to inform national bioenergy policies and research, development, and deployment strategies. It is the first volume in a two-volume set. Volume 2 evaluates the potential environmental sustainability effects of a subset of production scenarios described in Volume 1.
Producing renewable fuel from dedicated energy crops, such as switchgrass, has the potential to generate localized environmental benefits. This study uses high-resolution spatial data for west Tennessee to quantify the effects of producing switchgrass for cellulosic ethanol on the grey water footprint (GWF), or the amount of freshwater needed to dilute nitrate leachate to a safe level, relative to existing agricultural production. In addition, the estimated cost and GWF are incorporated in a mixed-integer multi-objective optimization model to derive the efficient frontier of the feedstock supply chain and determine a switchgrass supply chain that achieves the greatest reduction in GWF at the lowest cost. Results suggest that background nitrate concentration in ambient water and the types of agricultural land converted to switchgrass production influence the extent of the GWF. The average GWF of switchgrass in the study area ranges between 131.8 L L−1 and 145.9 L L−1 of ethanol, which falls into the range of estimated GWF of other lignocellulosic biomass feedstock in the literature. Also, the average cost of reducing GWF from the feedstock supply chain identified by the compromise solution method is $0.94 m−3 in the region. A tradeoff between biofuel production costs and reduced nitrate loading in groundwater is driven by differences in the agricultural land converted to feedstock production. Our findings illustrate the energy-water-food nexus in the development of a local bioenergy sector and provide a management strategy associated with land use choices for the supply of energy crops. However, the water quality improvements associated with displacing crop with feedstock production in one region could be offset by expanded or more intensive agricultural production in other regions.
Switchgrass (Panicum virgatum L.), a native of the North American prairies, has been selected for bioenergy research. With a focus on biomass yield improvement, this study aim (i) to estimate the genetic variation in biomass yield and important agronomic traits in ‘Alamo’, (ii) to determine correlations between biomass yield and agronomic traits, and (iii) to compare efficiency of phenotypic selection from a sward plot and advanced cycle half-sibs (ACHS) on the basis of space-plant performance. Sixty-two Alamo half-sib families (AHS) from a 4-yr-old Alamo sward and 20 advanced cycle half-sib families (ACHS) were evaluated in replicated field trials under simulated swards in Knoxville and Crossville, TN. Results showed significant variation (P < 0.05) among AHS for biomass yield, tillering ability, and spring vigor, suggesting the importance of additive genetic variation in these traits. Overall mean biomass yield of AHS was not different from the Alamo control, demonstrating the inefficiency of phenotypic selection from swards. Mean biomass yield of ACHS was 15 and 20% less than that of the control and AHS, respectively. Such results could be attributable to the influence of environment and genotype × environment interaction. However, results showed great potential for biomass yield improvement through selection on the basis of family performance. Using 10% selection intensity, parental control of two, and a narrow-sense heritability estimate of 0.11, gain per cycle selection from half-sib family selection is estimated to be 23%. Spring vigor showed potential use for indirect selection due to its high genetic correlation (rG = 0.75) with biomass yield. However, it is impeded by the low heritability estimate (h2 = 0.34).
on environment friendly and socio-economically sustainable renewable energy sources. However, commercial production of bioenergy is constrained by biomass supply uncertainty and associated costs. This study presents an integrated approach to determining the optimal biofuel supply chain considering biomass yield uncertainty. A two-stage stochastic mixed integer linear programming is utilized to minimize the expected system cost while incorporating yield uncertainty in the strategic level decisions related to biomass production and biorefinery investment.
Despite of the key role that short rotation woody crops (SRWC) play in supporting bioenergy and the bioeconomy, questions arise about the sustainability of bioenergy. Is it net energy efficient? Is bioenergy carbon neutral? Do SRWC plantations adversely affect food security by competing for land with agriculture? How will SRWC affect biodiversity and provision of environmental services? Answers are elusive and definitive answers require considering specific technology applied at a specific location. Thus, identifying where dedicated SRWC plantations would be viable in terms of biological productivity and economic attractiveness is a necessary first step in order to begin assessing their sustainability. We present a modeling framework using a process-based growth model, 3PG, and geographic information system technology to begin to answer sustainability questions about bioenergy plantations in the southern United States. We assessed potential profitability of four candidate SRWC species, Pinus taeda, Populus deltoides, Eucalyptus grandis, and Eucalyptus benthamii. Estimated yield (mean annual increment) was evaluated as internal rate of return on investment and land expectation value at the 5-digit ZIP code tabulation area level for 13 southern states. The 3PG model incorporates data on weather, soil, and species specific parameters to estimate potential volume production. This approach can be used for as a coarse filter for bioenergy projects that are under construction, in operation, proposed, or where due-diligence is required and to guide more detailed investigations in bioenergy siting-decision support systems. This approach will be most useful for choosing species to plant on former farmland or where landowners may be willing to change species on cutover forestland. The flexibility of the 3PG model allows for different climate scenarios to be developed and to assess risk of failure or lowered yields from extreme events such as drought, as well as altered future climate effects on sustainability. The silvicultural regime used in the model represents current and emerging practice; however, many feasible management regimes and site adaptations have been proposed. For example, the well-developed value chain for loblolly pine in the southern US provide opportunities for diverse silvicultural systems that could incorporate other biomass/bioenergy components, in addition to dedicated SRWC. The yield estimates can be used for further research on sustainability of carbon sequestration. The approach is useful generally as long as sufficient information on species traits is available to model productivity, silvicultural information to estimate management costs, and spatially explicit data on climate, environmental, and growing site conditions exists.