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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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.
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.
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.