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.
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.
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.
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 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.
The Energy Independence and Security Act (EISA) of 2007 was an omnibus energy policy law designed
to move the United States toward greater energy security and independence. A key provision of EISA is
the Renewable Fuel Standard (RFS) which requires the nation to use 36 billion gallons of renewable fuel
in vehicles by 2022. Ethanol is the most widely used renewable fuel, and a significant portion of the
36 billion gallon goal can be achieved by increasing the ethanol in gasoline to 15%. In fact in March
The model is a vehicle fuel-cycle model for transportation systems. The model provides a set of outcomes that would involve feedstock production, biorefinery production, storage and consumer demand as the complete fuel-cycle. The data is internal to the model, but might be adaptive to different biofuels specifications. This model was developed by the Energy Systems Division at Argonne National Laboratory.