KDF Search Results

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

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.

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

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.

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.

Using System Dynamics to Model the Transition to Biofuels in the United States Preprint, B. Bush, M. Duffy, and D. Sandor, National Renewable Energy Laboratory S. Peterson, Peterson Group To be presented at the Third International Conference on Systems of Systems Engineering Monterey, California June 2-4, 2008 Conference Paper NREL/CP-150-43153 June 2008

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?

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

IN THEIR REPORTS IN THE 29 FEBRUARY ISSUE (“LAND CLEARING AND THE BIOFUEL CARBON debt,” J. Fargione et al., p. 1235, and “Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change,” T. Searchinger et al., p. 1238), the authors do not provide adequate support for their claim that biofuels cause high emissions due to land-use change. The conclusions of both papers depend on the misleading premise that biofuel production causes forests and grasslands to be converted to agriculture.

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).

This paper presents a range of future, spatially explicit, land use change scenarios for the EU15, Norway and Switzerland based on an interpretation of the global storylines of the Intergovernmental Panel on Climate Change (IPCC) that are presented in the special report on emissions scenarios (SRES). The methodology is based on a qualitative interpretation of the SRES storylines for the European region, an estimation of the aggregate totals of land use change using various land use change models and the allocation of these aggregate quantities in space using spatially explicit rules.

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 tools to support the analysis of the causes and consequences of land use dynamics. Scenario analysis with land use models can support land use planning and policy. Numerous land use models are available, developed from different disciplinary backgrounds. This paper reviews current models to identify priority issues for future land use change modelling research.

The U.S. Departments of Agriculture and Energy jointly analyzed the economic potential for, and impacts of, large-scale bioenergy crop production in the United States. An agricultural sector model (POLYSYS) was modified to include three potential bioenergy crops (switchgrass, hybrid poplar, and willow). At farmgate prices of US $2.44/GJ, an estimated 17 million hectares of bioenergy crops, annually yielding 171 million dry Mg of biomass, could potentially be produced at a profit greater than existing agricultural uses for the land.

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.