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.
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This article connects the science of sustainability theory with applied aspects of sustainability deployment. A suite of 35 sustainability indicators spanning 12 environmental and socioeconomic categories has been proposed for comparing the sustainability of bioenergy production systems across different feedstock types and locations.
The Paris Agreement and the EU Climate and Energy Framework set ambitious but necessary targets. Reducing greenhouse gas (GHG) emissions by phasing out the technologies and infrastructures that cause fossil carbon emissions is one of today’s most important challenges. In the EU, bioenergy is currently the largest renewable energy source used. Most Member States have in absolute terms increased the use of forest biomass for energy to reach their 2020 renewable energy targets.
Social and economic indicators can be used to support design of sustainable energy systems. Indicators representing categories of social well-being, energy security, external trade, profitability, resource conservation, and social acceptability have not yet been measured in published sustainability assessments for commercial algal biofuel facilities.
Renewable, biomass-based energy options can reduce the climate impacts of fossil fuels.
This report is a collective effort of the Scientific Committee on Problems of the Environment (SCOPE), including contributions from 137 researchers of 82 institutions in 24 countries. It concludes that land availability is not a limiting factor to bioenergy production and that bioenergy can contribute to sustainable energy supplies even with increasing food demands, preservation of forests, protected lands, and rising urbanization.
Water consumption and water quality continue to be key factors affecting environmental sustainability in biofuel production. This review covers the findings from biofuel water analyses published over the past 2 years to underscore the progress made, and to highlight advancements in understanding the interactions among increased production and water demand, water resource availability, and potential changes in water quality. We focus on two key areas: water footprint assessment and watershed modeling.
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.
The compatibility of elastomeric materials used in fuel storage and dispensing applications was determined for test fuels
representing neat gasoline and gasoline blends containing 10 and 17 vol.% ethanol, and 16 and 24 vol.% isobutanol. The
actual test fuel chemistries were based on the aggressive formulations described in SAE J1681 for oxygenated gasoline.
Elastomer specimens of fluorocarbon, fluorosilicone, acrylonitrile rubber (NBR), polyurethane, neoprene, styrene
The compatibility of plastic materials used in fuel storage and dispensing applications was determined for test fuels representing gasoline blended with 25 vol.% ethanol and gasoline blended with 16 and 24 vol.% isobutanol. Plastic materials included those used in flexible plastic piping and fiberglass resins. Other commonly used plastic materials were also evaluated. The plastic specimens were exposed to Fuel C, CE25a, CiBu16a, and CiBu24a for 16 weeks at 60oC.
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
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.
This article summarises the compatibility of six elastomers – used in fuel
storage and delivery systems – with test fuels representing gasoline blended
with up to 85% ethanol. Individual coupons were exposed to test fuels for four
weeks to achieve saturation. The change in volume and hardness, when wetted
and after drying, were measured and compared with the original condition.
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
Developing scientific criteria and indicators should play a critical role in charting a sustainable path for the rapidly developing biofuel industry. The challenge ahead in developing such criteria and indicators is to address the limitations on data and modeling.
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.
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.
Biomass power offers utilities a potential pathway to increase their renewable generation portfolios for compliance with renewable energy standards and to reduce greenhouse gas (GHG) emissions relative to current fossil-based technologies. To date, a large body of life-cycle assessment (LCA) literature assessing biopower’s life-cycle GHG emissions has been published.