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Transgenic modification of plants is a key enabling technology for developing sustainable biofeedstocks for biofuels production. Regulatory decisions and the wider acceptance and development of transgenic biofeedstock crops are considered from the context of science-based risk assessment. The risk assessment paradigm for transgenic biofeedstock crops is fundamentally no different from that of current generation transgenic crops, except that the focus of the assessment must consider the unique attributes of a given biofeedstock crop and its environmental release.

Soaring global food prices are threatening to push more poor people back below the poverty line; this will probably become aggravated by the serious challenge that increasing population and climate changes are posing for food security. There is growing evidence that human activities involving fossil fuel consumption and land use are contributing to greenhouse gas emissions and consequently changing the climate worldwide. The finite nature of fossil fuel reserves is causing concern about energy security and there is a growing interest in the use of renewable energy sources such as biofuels.

The rapidly expanding biofuel industry has changed the fundamentals of U.S. agricultural commodity markets. Increasing ethanol and biodiesel production has generated a fast-growing demand for corn and soybean products, which competes with the well-established domestic livestock industry and foreign buyers. Meanwhile, the co-products of biofuel production are replacing or displacing coarse grains and oilseed meal in feed rations for livestock.

Prior studies have estimated that a liter of bioethanol requires 263−784 L of water from corn farm to fuel pump, but these estimates have failed to account for the widely varied regional irrigation practices. By using regional time-series agricultural and ethanol production data in the U.S., this paper estimates the state-level field-to-pump water requirement of bioethanol across the nation. The results indicate that bioethanol’s water requirements can range from 5 to 2138 L per liter of ethanol depending on regional irrigation practices.

There is a strong societal need to evaluate and understand the sustainability of biofuels, especially because of the significant increases in production mandated by many countries, including the United States. Sustainability will be a strong factor in the regulatory environment and investments in biofuels. Biomass feedstock production is an important contributor to environmental, social, and economic impacts from biofuels.

The water consumption and agrochemical use during biofuel production could adversely impact both availability and quality of a precious resource.

In this paper, we assess what is known or anticipated about environmental and sustainability factors associated with next-generation biofuels relative to the primary conventional biofuels (i.e., corn grain-based ethanol and soybean-based diesel) in the United States during feedstock production and conversion processes. Factors considered include greenhouse (GHG) emissions, air pollutant emissions, soil health and quality, water use and water quality, wastewater and solid waste streams, and biodiversity and land-use changes.

A method is presented, which estimates the potential for power production from agriculture residues. A GIS decision support system (DSS) has been developed, which implements the method and provides the tools to identify the geographic distribution of the economically exploited biomass potential. The procedure introduces a four level analysis to determine the
theoretical, available, technological and economically exploitable potential. The DSS handles all possible restrictions and

The use of Geographic Information Systems (GIS) for understanding the geographic context of bioenergy supplies is discussed and a regional-scale, GIS-based modeling system for estimating potential biomass supplies from energy crops is described. While GIS models can capture geographic variation that may in?uence biomass costs and supplies, GIS models are not likely to handle uncertainty well and are often limited by the lack of spatially explicit data.

The U.S. Geological Survey (USGS) 2001 National Land Cover Database (NLCD) was compared to the U.S. Department of Agriculture (USDA) 2002 Census of Agriculture. Wecompared areal estimates for cropland at the state and county level for 14 States in the Upper Midwest region of the United States. Absolute differences between the NLCD and Census cropland areal estimates at the state level ranged from 1.3% (Minnesota) to 37.0% (Wisconsin). The majority of counties (74.5%) had differences of less than 100 km2. 7.2% of the counties had differences of more than 200 km2.

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level.

Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends.

When fuelwood is harvested at a rate exceeding natural growth and inefficient conversion technologies are used, negative environmental and socio-economic impacts, such as fuelwood shortages, natural forests degradation and net GHG emissions arise. In this study, we argue that analyzing fuelwood supply/demand spatial patterns require multiscale approaches to effectively bridge the gap between national results with local situations.

Greenhouse gas release from land use change (the socalled ?carbon debt?) has been identified as a potentially significant contributor to the environmental profile of biofuels. The time required for biofuels to overcome this carbon debt duetolandusechangeandbeginprovidingcumulativegreenhouse gas benefits is referred to as the ?payback period? and has been estimated to be 100-1000 years depending on the specific ecosystem involved in the land use change event. Two mechanisms for land use change exist: ?direct?

Two of the most widely used land-cover data sets for the United States are the National Land-Cover Data (NLCD) at 30-m resolution and the Global Land- Cover Characteristics (GLCC) at 1-km nominal resolution. Both data sets were produced around 1992 and expected to provide similar land-cover information. This study investigated the spatial distribution of NLCD within major GLCC classes at 1-km unit over a total of 11 agricultural-related eco-regions across the continental United States.