KDF Search Results

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long‐term production potentials in the United states.

Energy market conditions have shifted dramatically since the USA renewable fuel standards (RFS1 in 2005; RFS2 in 2007) were enacted. The USA has transitioned from an increasing dependence on oil imports to abundant domestic oil production. In addition, increases in the use of ethanol, the main biofuel currently produced in the USA, is now limited by the blend wall constraint. Given this, the current study evaluates alternative biofuel deployment scenarios in the USA, accounting for changes in market conditions.

This analysis estimates the cost of selected oil and biomass supply shocks for producers and consumers in the light-duty vehicle fuel market under various supply chain configurations using a mathematical programing model, BioTrans. The supply chain configurations differ by whether they include selected flexibility levers: multi-feedstock biorefineries; advanced biomass logistics; and the ability to adjust ethanol content of low-ethanol fuel blends, from E10 to E15 or E05.

We explore the role of biofuels in mitigating the negative impacts of oil supply shocks on fuel markets under a range of oil price trajectories and biofuel blending mandate levels. Using a partial equilibrium model of US biofuels production and petroleum fuels trade, we discuss the adjustments in light‐duty vehicle fuel mix, fuel prices, and renewable identification number (RIN) prices following each shock as well as the distribution of shock costs across market participants. Ethanol is used as both a complement (blend component in E10) and a substitute (in E15 and E85 blends) to gasoline.

Price Scenarios at $54 and $119 were simulated for Switchgrass, Miscanthus and Willow production from 2017 to 2040. These analyses were used in Woodbury, Peter B., et al. 2018. "Improving water quality in the Chesapeake Bay using payments for ecosystem services for perennial biomass for bioenergy and biofuel production." Biomass and Bioenergy 114:132-142. doi: https://doi.org/10.1016/j.biombioe.2017.01.024.

This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply.

Synthesis manuscript for an Ecology & Society Special Feature on Telecoupling: A New Frontier for Global Sustainability

The ongoing debate about costs and benefits of wood‐pellet based bioenergy production in the southeastern United States (SE USA) requires an understanding of the science and context influencing market decisions associated with its sustainability. Production of pellets has garnered much attention as US exports have grown from negligible amounts in the early 2000s to 4.6 million metric tonnes in 2015. Currently, 98% of these pellet exports are shipped to Europe to displace coal in power plants.

Wood pellet exports from the Southeastern United States (SE US) to Europe have been increasing in response to European Union member state policies to displace coal with renewable biomass for electricity generation. An understanding of the interactions among SE US forest markets, forest management, and forest ecosystem services is required to quantify the effects of pellet production compared to what would be expected under a reference case or ‘counterfactual scenario’ without pellet production.

In order to understand the climate effects of a bioenergy system, a comparison between the bioenergy system and a reference system is required. The reference system describes the situation that occurs in the absence of the bioenergy system with respect to the use of land, energy, and materials. The importance of reference systems is discussed in the literature but guidance on choosing suitable reference systems for assessing climate effects of bioenergy is limited. The reference system should align with the purpose of the study.

Published in Bioenergy and Land Use Change (pp. 141–153). John Wiley & Sons, Inc.

Simulated Response of Avian Biodiversity to Biomass Production. 2017. Chapter 10 in R.A. Efroymson et al. eds., 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 2: Environmental Sustainability Effects of Select Scenarios from Volume 1. ORNL/TM-2016/727. Oak Ridge National Laboratory, Oak Ridge, TN, pp.140-182. DOI: 10.2172/1338837, https://energy.gov/eere/bioenergy/downloads/2016-billion-ton-report-vol…

Jager, H. I., M. Wu, M. Ha, L. Baskaran and J. Krieg. 2017. Water Quality Responses to Simulated Management Practices on Agricultural Lands Producing Biomass Feedstocks in Two Tributary Basins of the Mississippi River, in R.A. Efroymson et al. eds., 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 2: Environmental Sustainability Effects of Select Scenarios from Volume 1. ORNL/TM-2016/727. Oak Ridge National Laboratory, Oak Ridge, TN, pp.140-182.

Abstract

Abstract

We implemented the Soil and Water Assessment Tool (SWAT) to simulate water quantity and quality for the Arkansas-White-Red (AWR) river basin. We used the 2009 Cropland Data Layer (CDL-2009) (USDA-NASS, 2009) to represent the baseline (i.e., Scenario Base) land use/land cover. The SWAT model was calibrated and validated under Scenario Base (refer to Baskaran et al. (2010) for details). We further applied SWAT to project water quantity and quality under Scenario BC1 by replacing the baseline land cover with corresponding future land cover.

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).