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.
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 paper describes an approach to landscape design that focuses on integrating bioenergy production with their components of environmental, social and economic systems. Landscape design as used here refers to a spatially explicit, collaborative plan for management of landscapes and supply chains. Landscape design can involve multiple scales and build on existing practices to reduce costs or enhance services.
Understanding how large-scale bioenergy production can affect biodiversity and ecosystems is important if society is to meet current and future sustainable development goals. A variety of bioenergy production systems have been established within different contexts throughout the Pan American region, with wide-ranging results in terms of documented and projected effects on biodiversity and ecosystems.
As with all land transformation activities, effects on biodiversity and ecosystem services of producing feedstocks for biofuels are highly variable and context specific. Advances toward more sustainable biofuel production benefit from a system's perspective, recognizing spatial heterogeneity and scale, landscape-design principles, and addressing the influences of context such as the particular products and their distribution, policy background, stakeholder values, location, temporal influences, and baseline conditions. Deploying biofuels in a manner to reduce effects on biodiversity
The US Congress passed the Renewable Fuels Standard (RFS) seven years ago. Since then, biofuels have gone from darling to scapegoat for many environmentalists, policy makers, and the general public. The reasons for this shift are complex and include concerns about environmental degradation, uncertainties about impact on food security, new access to fossil fuels, and overly optimistic timetables. As a result, many people have written off biofuels.
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.
Landscape ecology focuses on the spatial patterns and processes of ecological and human interactions. These patterns and processes are being altered by both changing resource-management practices of humans and changing climate conditions associated, in part, with increases in atmospheric concentrations of greenhouse gases. Dominant resource-extraction and land-management activities involve energy, and the use of fossil energy is one of the key drivers behind increasing greenhouse gas emissions as well as land-use changes.
T. Searchinger et al. propose "Fixing a critical climate accounting error" (Policy Forum, 23 October 2009, p. 527). We agree that greenhouse gas (GHG) emission accounting needs to be more comprehensive, but believe that Searchinger's proposal would make matters worse by increasing the complexity and uncertainty of calculations. Solutions must be practical and verifiable to be effective.
We present a system dynamics global LUC model intended to examine LUC attributed to biofuel production. The model has major global land system stocks and flows and can be exercised under different food and biofuel demand assumptions. This model provides insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy rather than a precise number generator.
The link provides data and reports related to bioenergy - ethanol and biodiesel produced by Minnesota.