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.

In January 2017, the U.S. Department of Energy’s (DOE’s) Bioenergy Technologies Office (BETO) published a report, titled Biofuels and Bioproducts from Wet and Gaseous Waste Streams: Challenges and Opportunities.

Understanding the complex interactions among food security, bioenergy sustainability, and resource management
requires a focus on specific contextual problems and opportunities. The United Nations’ 2030 Sustainable
Development Goals place a high priority on food and energy security; bioenergy plays an important role in
achieving both goals. Effective food security programs begin by clearly defining the problem and asking, ‘What
can be done to assist people at high risk?’ Simplistic global analyses, headlines, and cartoons that blame biofuels

Quantifying lignin and carbohydrate composition of corn (Zea mays L.) is important to support the emerging cellulosic biofuels industry. Therefore, field studies with 0 or 100 % stover removal were established in Alabama and South Carolina as part of the Sun Grant Regional Partnership Corn Stover Project. In Alabama, cereal rye (Secale cereale L.) was also included as an additional experimental factor, serving as a winter cover crop.

Water consumption and water quality continue to be key factors affecting environmental sustainability in biofuel production. This review covers the findings from biofuel water analyses published over the past 2 years to underscore the progress made, and to highlight advancements in understanding the interactions among increased production and water demand, water resource availability, and potential changes in water quality. We focus on two key areas: water footprint assessment and watershed modeling.

This paper describes the current Biomass Scenario Model (BSM) as of August 2013, a system dynamics model developed under the support of the U.S. Department of Energy (DOE). The model is the result of a multi-year project at the National Renewable Energy Laboratory (NREL). It is a tool designed to better understand biofuels policy as it impacts the development of the supply chain for biofuels in the United States.

The present study experimentally investigates spark-ignited combustion with 87 AKI E0 gasoline in its neat form
and in midlevel alcohol−gasoline blends with 24% vol/vol isobutanol−gasoline (IB24) and 30% vol/vol ethanol−gasoline (E30).
A single-cylinder research engine was used with an 11.85:1 compression ratio, hydraulically actuated valves, laboratory intake air,
and was capable of external exhaust gas recirculation (EGR). Experiments were conducted with all fuels to full-load conditions

The present study experimentally investigates spark-ignited combustion with 87 AKI E0 gasoline in its neat form
and in midlevel alcohol−gasoline blends with 24% vol/vol isobutanol−gasoline (IB24) and 30% vol/vol ethanol−gasoline (E30).
A single-cylinder research engine is used with an 11.85:1 compression ratio, hydraulically actuated valves, laboratory intake air,
and was capable of external exhaust gas recirculation (EGR). Experiments were conducted with all fuels to full-load conditions

n the past decades, the production of biomass for energy in agriculture and forestry has increased in many parts of the world. For years to come, further increase in land use for bioenergy will be needed to meet the renewable energy ambitions of many countries, and to reduce fossil fuel use and associated GHG emissions.

Biofuels are promoted in the United States through aggressive legislation, as one part of an overall strategy to lessen dependence on imported energy as well as to reduce the emissions of greenhouse gases (Office of the Biomass Program and Energy Efficiency and Renewable Energy, 2008). For example, the Energy Independence and Security Act of 2007 (EISA) mandates 36 billion gallons of renewable liquid transportation fuel in the U.S. marketplace by the year 2022 (U.S. Government, 2007).

The global indirect land use change (ILUC) implications of biofuel use in the United States of America (USA) from 2001 to 2010 are evaluated with a dynamic general equilibrium model.  The effects of biofuels production on agricultural land area vary by year; from a net expansion of 0.17ha per 1000 gallons produced (2002) to a net contraction of 0.13ha per 1000 gallons (2018) in Case 1 of our simulation.  In accordance with the general narrative about the implications of biofuel policy, agricultural land area increased in many regions of the world.  However, oil-export dependent economies e

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.

Relationships between people and their environment are largely defined by land use. Space and soil are needed for native plants and wildlife, as well as for crops used for food, feed, fiber, wood products and biofuel (liquid fuel derived from plant material). People also use land for homes, schools, jobs, transportation, mining and recreation. Social and economic forces influence the allocation of land to various uses.

Relationships between people and their environment are largely defined by land use. Space and soil are needed for native plants and wildlife, as well as for crops used for food, feed, fiber, wood products and biofuel (liquid fuel derived from plant material). People also use land for homes, schools, jobs, transportation, mining and recreation. Social and economic forces influence the allocation of land to various uses. The

Developing scientific criteria and indicators should play a critical role in charting a sustainable path for the rapidly developing biofuel industry. The challenge ahead in developing such criteria and indicators is to address the limitations on data and modeling.

Despite recent claims to the contrary, plant-based fuels developed in economically and environmentally sensible ways can contribute significantly to the nation’s— indeed, the world’s—energy security while providing a host of benefits for many people worldwide.

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?

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).