KDF Search Results

The goal of this repository is to promote transparency and ease-of-access to the U.S. Department of Energy Bioenergy Technologies Office (BETO) supported public studies involving techno-economic analysis (TEA). As such, this database summarizes the economic and technical parameters associated with the modeled biorefinery processes for the production of biofuels and bioproducts, as presented in a range of published reports and papers.

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.

United States is experiencing increasing interests in fermentation and anaerobic digestion processes for the production of biofuels. A simple methodology of spatial biomass assessment is presented in this paper to evaluate biofuel production and support the first decisions about the conversion technology applications. The methodology was applied to evaluate the potential biogas and ethanol production from biomass in California and Washington states. Solid waste databases were filtered to a short list of digestible and fermentable wastes in both states.

Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and
long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of
the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water
Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a

We quantify the emergence of biofuel markets and its impact on U.S. and world agriculture for the coming decade using the multi-market, multi-commodity international FAPRI (Food and Agricultural Policy Research Institute) model. The model incorporates the trade-offs between biofuel, feed, and food production and consumption and international feedback effects of the emergence through world commodity prices and trade.

In recent years, considerable concern has been raised about the sustainability of the world's forested ecosystems (FAO, 2003). With deforestation rates in tropical regions estimated to be as high as 12 million hectares per year (FAO, 2003; Houghton, 2003), much of the concern has centered around tropical deforestation. In contrast to these developments in tropical areas, there is evidence that the area of forests in temperate regions is expanding.

The Center for Sustainability and the Global Environment (SAGE) at the University of Wisconsin has been developing global databases of contemporary and historical agricultural land use and land cover. SAGE has chosen to focus on agriculture because it is clearly the predominant land use activity on the planet today, and provides a vital service?i.e., food?for human societies. SAGE has developed a ?data fusion?

Land-use changes are frequently indicated to be one of the main human-induced factors influencing the groundwater system. For land-use change, groundwater research has mainly focused on the change in water quality thereby neglecting changes in quantity. The objective of this paper is to assess the impact of land-use changes, from 2000 until 2020, on the hydrological balance and in particular on groundwater quantity, as results from a case study in the Kleine Nete basin, Belgium.

Agricultural activities have dramatically altered our planet?s land surface. To understand the extent and spatial distribution of these changes, we have developed a new global data set of croplands and pastures circa 2000 by combining agricultural inventory data and satellite-derived land cover data. The agricultural inventory data, with much greater spatial detail than previously available, is used to train a land cover classification data set obtained by merging two different satellite-derived products (Boston University?s MODIS-derived land cover product and the GLC2000 data set).

The preceding two chapters of this volume have discussed physical and economic data bases for global agriculture and forestry, respectively. These form the foundation for the integrated, global land use data base discussed in this chapter. However, in order to utilize these data for global CGE analysis, it is first necessary to integrate them into a global, general equilibrium data base. This integration is the subject of the present chapter

This study presents the results of comparing land use estimates between three different data sets for the Upper Mississippi River Basin (UMRB). The comparisons were performed between the U.S. Department of Agriculture (USDA) Natural Resource Conservation Service (NRCS) National Resource Inventory (NRI), the U.S. Geological Survey (USGS) National Land Cover Data (NLCD) database, and a combined USDA National Agricultural Statistics Service (NASS) Agricultural Census – NLCD dataset created to support applications of the Hydrologic Unit Model for the U.S. (HUMUS).

National interests in greater energy independence, concurrent with favorable market forces, have driven increased production of corn-based ethanol in the United States and research into the next generation of biofuels. The trend is changing the national agricultural landscape and has raised concerns about potential impacts on the nation?s water resources. This report examines some of the key issues and identifies opportunities for shaping policies that help to protect water resources.

This paper describes the GTAP land use data base designed to support integrated assessments of the potential for greenhouse gas mitigation. It disaggregates land use by agro-ecological zone (AEZ). To do so, it draws upon global land cover data bases, as well as state-of-the-art definition of AEZs from the FAO and IIASA. Agro-ecological zoning segments a parcel of land into smaller units according to agro-ecological characteristics, including: precipitation, temperature, soil type, terrain conditions, etc. Each zone has a similar combination of constraints and potential for land use.

The paper describes the on-going project of the GTAP land use data base. We also present the GTAPE-AEZ model, which illustrates how land use and land-based emissions can be incorporated in the CGE framework for Integrated Assessment (IA) of climate change policies. We follow the FAO fashion of agro-ecological zoning (FAO, 2000; Fischer et al, 2002) to identify lands located in six zones. Lands located in a specific AEZ have similar (or homogenous) soil, landform and climatic characteristics.

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution.

Land-use change models are used by researchers and professionals to explore the dynamics and drivers of land-use/land-cover change and to inform policies affecting such change. A broad array of models and modeling methods are available to researchers, and each type has certain advantages and disadvantages depending on the objective of the research. This report presents a review of different types of models as a means of exploring the functionality and ability of different approaches.

This paper presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas.

Until recently, advanced very high-resolution radiometer (AVHRR) observations were the only viable source of data for global land cover mapping. While many useful insights have been gained from analyses based on AVHRR data, the availability of moderate resolution imaging spectroradiometer (MODIS) data with greatly improved spectral, spatial, geometric, and radiometric attributes provides significant new opportunities and challenges for remote sensing-based land cover mapping research.

The Energy Independence and Security Act (EISA) of 2007 established specific targets for the production of biofuel in the United States. Until advanced technologies become commercially viable, meeting these targets will increase demand for traditional agricultural commodities used to produce ethanol, resulting in land-use, production, and price changes throughout the farm sector. This report summarizes the estimated effects of meeting the EISA targets for 2015 on regional agricultural production and the environment. Meeting EISA targets for ethanol production is estimated to expand U.S.