Reducing dependence on fossil‐based energy has raised interest in biofuels as a potential energy source, but concerns have been raised about potential implications for water quality. These effects may vary regionally depending on the biomass feedstocks and changes in land management. Here, we focused on the Tennessee River Basin (TRB), USA.
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Price Scenarios at $54 and $119 were simulated for Switchgrass, Miscanthus and Willow production from 2017 to 2040. These analyses will be used in a subsequent publication.
Net benefits of bioenergy crops, including maize and perennial grasses such as switchgrass, are a function of several factors including the soil organic carbon (SOC) sequestered by these crops. Life cycle assessments (LCA) for bioenergy crops have been conducted using models in which SOC information is usually from the top 30 to 40 cm. Information on the effects of crop management practices on SOC has been limited so LCA models have largely not included any management practice effects.
Abstract: Unfavorable weather can significantly impact the production and provision of agriculture-based biomass feedstocks such as Miscanthus and switchgrass. This work quantified the impact of regional weather on the feedstock production systems using the BioFeed modeling framework. Weather effects were incorporated in BioFeed by including the probability of working day (pwd) parameter in the model, which defined the fraction of days in a specific period such as two weeks that were suitable for field operations.
The increasing demand for bioenergy crops presents our society with the opportunity to design more sustainable landscapes. We have created a Biomass Location for Optimal Sustainability Model (BLOSM) to test the hypothesis that landscape design of cellulosic bioenergy crop plantings may simultaneously improve water quality (i.e. decrease concentrations of sediment, total phosphorus, and total nitrogen) and increase profits for farmer-producers while achieving a feedstock-production goal.
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
As the US begins to integrate biomass crops and residues into its mix of energy feedstocks, tools are needed to measure the long-term sustainability of these feedstocks. Two aspects of sustainability are long-term potential for profitably producing energy and protection of ecosystems influenced by energy-related activities. The Soil and Water Assessment Tool (SWAT) is an important model used in our efforts to quantify both aspects. To quantify potential feedstock production, we used SWAT to estimate switchgrass yields at a national scale.
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?
In response to concerns about oil dependency and the contributions of fossil fuel use to climatic change, the U.S. Department of Energy has begun a research initiative to make 20% of motor fuels biofuel based in 10 years, and make 30% of fuels bio-based by 2030. Fundamental to this objective is developing an understanding of feedstock dynamics of crops suitable for cellulosic ethanol production. This report focuses on switchgrass, reviewing the existing literature from field trials across the United States, and compiling it for the first time into a single database.
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