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.
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
Reducing dependence on fossil‐based energy has raised interest in biofuels as a potential energy source, but concerns have been raised about potential implications for water quality. These effects may vary regionally depending on the biomass feedstocks and changes in land management. Here, we focused on the Tennessee River Basin (TRB), USA.
Price Scenarios at $54 and $119 were simulated for Switchgrass, Miscanthus and Willow production from 2017 to 2040. These analyses were used in Woodbury, Peter B., et al. 2018. "Improving water quality in the Chesapeake Bay using payments for ecosystem services for perennial biomass for bioenergy and biofuel production." Biomass and Bioenergy 114:132-142. doi: https://doi.org/10.1016/j.biombioe.2017.01.024.
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)
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.
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.
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
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
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.
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.
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
ABSTRACT. Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a regional scale.
Discussions of alternative fuel and propulsion technologies for transportation often overlook the infrastructure required to make these options practical and cost-effective. We estimate ethanol production facility locations and use a linear optimization model to consider the economic costs of distributing various ethanol fuel blends to all metropolitan areas in the United States. Fuel options include corn-based E5 (5% ethanol, 95% gasoline) to E16 from corn and switchgrass, as short-term substitutes for petroleum-based fuel.
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.