KDF Search Results

We propose a causal analysis framework to increase understanding of land-use change (LUC) and the reliability of LUC models. This health-sciences-inspired framework can be applied to determine probable causes of LUC in the context of bioenergy. Calculations of net greenhouse gas (GHG) emissions for LUC associated with biofuel production are critical in determining whether a fuel qualifies as a biofuel or advanced biofuel category under regional (EU), national (US, UK), and state (California) regulations.

Conventional feedstock supply systems exist and have been developed for traditional agriculture and forestry systems. These conventional feedstock supply systems can be effective in high biomass-yielding areas (such as for corn stover in Iowa and plantation-grown pine trees in the southern United States), but they have their limits, particularly with respect to addressing feedstock quality and reducing feedstock supply risk to biorefineries. They also are limited in their ability to efficiently deliver energy crops.

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.

The Alternative Fuels Data Center (AFDC) provides information, data, and tools to help fleets and other transportation decision makers find ways to reduce petroleum consumption through the use of alternative and renewable fuels, advanced vehicles, and other fuel-saving measures.

The Census of Agriculture, taken every five years, is a complete count of U.S. farms and ranches and the people who operate them. The Census looks at land use and ownership, operator characteristics, production practices, income and expenditures. For America’s farmers and ranchers, the Census of Agriculture is their voice, their future and their responsibility.

This report, generally referred to as the Billion-Ton Study or 2005 BTS, is an estimate of “potential” biomass available within the contiguous United States based on assumptions about inventory production capacity, availability, and technology.