The economic potential for Eucalyptus spp. production for jet fuel additives in the United States: A 20 year projection suite of scenarios ranging from $110 Mg-1 to $220 Mg-1 utilizing the POLYSYS model.
Link to the website with documentation and download instructions for the PNNL Global Change Assessment Model (GCAM), a community model or long-term, global energy, agriculture, land use, and emissions. BioEnergy production, transformation, and use is an integral part of GCAM modeling and scenarios.
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
This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply.
We propose a causal analysis framework to increase understanding of land-use change (LUC) and the reliability of LUC models. This health-sciences-inspired framework can be applied to determine probable causes of LUC in the context of bioenergy. Calculations of net greenhouse gas (GHG) emissions for LUC associated with biofuel production are critical in determining whether a fuel qualifies as a biofuel or advanced biofuel category under regional (EU), national (US, UK), and state (California) regulations.
Potential Avenues for High Biofuels Penetration in the U.S. Aviation Market, Supplemental Tableau Workbook, 2016
Emily Newes, National Renewable Energy Laboratory Jeongwoo Han, Argonne National Laboratory Steve Peterson, Lexidyne LLC
The development of modern high efficiency bioenergy technologies has the
potential to improve energy security and access while reducing environmental impacts
and stimulating low-carbon development. While modern bioenergy production is
increasing in the world, it still makes a small contribution to our energy matrix.
At present, approximately 87% of energy demand is satisfied by energy produced
through consumption of fossil fuels. Although the International Energy Agency (IEA)
Peer-reviewed letter written in response to a March 11, 2015, letter to US EPA Administrator Gina McCarthy (http://bit.ly/1HsSaWf), in which the Ecological Society of America objected to EPA’s proposal that sustainably harvested woody biomass could reduce carbon emissions.
For analyzing sustainability of algal biofuels, we identify 16 environmental indicators that fall into six categories: soil quality, water quality and quantity, air quality, greenhouse gas emissions, biodiversity, and productivity. Indicators are selected to be practical, widely applicable, predictable in response, anticipatory of future changes, independent of scale, and responsive to management.
Abstract: Farmgate prices (i.e. price delivered roadside ready for loading and transport) for biomass feedstocks directly infl uence biofuel prices. Using the latest available data, marginal (i.e. price for the last ton) farmgate prices of $51, $63, and $67 dry ton–1 ($2011) are projected as necessary to provide 21 billion gallons of biofuels from about 250 million dry tons of terrestrial feedstocks in 2022 under price-run deterministic, demand-run deterministic, and stochastic simulations, respectively.
A global energy crop productivity model that provides geospatially explicit quantitative details on biomass
potential and factors affecting sustainability would be useful, but does not exist now. This study describes a
modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling.
We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized
natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and
Potential global biodiversity impacts from near-term gasoline production are compared to biofuel, a renewable liquid transportation fuel expected to substitute for gasoline in the near term (i.e., from now until c.
This paper describes the current Biomass Scenario Model (BSM) as of August 2013, a system dynamics model developed under the support of the U.S. Department of Energy (DOE). The model is the result of a multi-year project at the National Renewable Energy Laboratory (NREL). It is a tool designed to better understand biofuels policy as it impacts the development of the supply chain for biofuels in the United States.
Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the spatial extent and temporal duration of ethanol and gasoline production processes and environmental effects based on a literature review and then synthesize the scale differences on space-time diagrams.
The Biomass Energy Data Book is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Biomass Program in the Energy Efficiency and Renewable Energy (EERE) program of the Department of Energy (DOE). Designed for use as a convenient reference, the book represents an assembly and display of statistics and information that characterize the biomass industry, from the production of biomass feedstocks to their end use, including discussions on sustainability.
This paper focuses ont he patterns of farmers' choices regarding dedicated perennial lignocellulosic energy crops. We focus on choices abou perennial crops because two thirds of the mandated advanced biofuels are expected to be converted at biorefineries from perennials (USDA 2010).
Indicators are needed to assess both socioeconomic and environmental sustainability of bioenergy systems. Effective indicators can help to identify and quantify the sustainability attributes of bioenergy options. We identify 16 socioeconomic indicators that fall into the categories of social well-being, energy security, trade, profitability, resource conservation, and social acceptability. The suite of indicators is predicated on the existence of basic institutional frameworks to provide governance, legal, regulatory and enforcement services.
Nationwide spatial dataset representing the polygon areas for first-generation suitability analysis of potentially suitable areas for microalgae open ponds. The PNNL microalgae growth model results for each site are included in the attribute table and assume growth based on theoretical limits. Sites represent a minimum mapping unit of 490 hectares. Land suitability included area less than or equal to 1% slope on non-agricultural, undeveloped or low‐density developed, nonsensitive, generally noncompetitive land was considered for microalgal culture facilities.
Microalgae are receiving increased global attention as a potential sustainable “energy crop”for biofuel production. An important step to realizing the potential of algae is quantifying the demands commercial‐scale algal biofuel production will place on water and land resources. We present a high‐resolution spatiotemporal assessment that brings to bear fundamental questions of where production can occur, how many land and water resources are required, and how much energy is produced.
Indicators are needed to assess environmental sustainability of bioenergy systems. Effective indicators
will help in the quantification of benefits and costs of bioenergy options and resource uses. We identify
19 measurable indicators for soil quality, water quality and quantity, greenhouse gases, biodiversity, air
quality, and productivity, building on existing knowledge and on national and international programs
that are seeking ways to assess sustainable bioenergy. Together, this suite of indicators is hypothesized