This project contributes to understanding and enhancing socioeconomic and environmental benefits of biofuels through modeling the effect of prices and policy incentives on fuel markets for “hard-to-decarbonize” transportation sectors. The main analytical tool used in this project is the BioTrans model, originally developed to assess and quantify the economic and energy security benefits of biofuels for light-duty vehicles and bioproducts.
Synthesis manuscript for an Ecology & Society Special Feature on Telecoupling: A New Frontier for Global Sustainability
This report provides a status of the markets and technology development involved in growing a domestic bioenergy economy as it existed at the end of calendar year 2013. It compiles and integrates information to provide a snapshot of the current state and historical trends influencing the development of bioenergy markets. This information is intended for policy-makers as well as technology developers and investors tracking bioenergy developments. It also highlights some of the key energy and regulatory drivers of bioenergy markets.
Social and economic indicators can be used to support design of sustainable energy systems. Indicators representing categories of social well-being, energy security, external trade, profitability, resource conservation, and social acceptability have not yet been measured in published sustainability assessments for commercial algal biofuel facilities.
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.
Meeting the Energy Independence and Security Act (EISA) renewable fuels goals requires development
of a large sustainable domestic supply of diverse biomass feedstocks. Macroalgae, also known as
seaweed, could be a potential contributor toward this goal. This resource would be grown in marine
waters under U.S. jurisdiction and would not compete with existing land-based energy crops.
Very little analysis has been done on this resource to date. This report provides information needed for an
This model was developed at Idaho National Laboratory and focuses on crop production. This model is an agricultural cultivation and production model, but can be used to estimate biomass crop yields.
NOAA's National Centers for Coastal Ocean Science's (NCCOS's) PCMHAB program funds research to move promising technologies for preventing, controlling, or mitigating HABs and their impacts through development, to demonstration, and, finally application, culminating in wide spread use in the field by end-users. A more detailed description of the program and its projects are available at the link below.
The U.S. biomass resource can be used several ways that provide domestic, renewable energy to users. Understanding the capacity of the biomass resource, its potential in energy markets, and the most economic utilization of biomass is important in policy development and project selection. This study analyzed the potential for biomass within markets and the competition between them.
Biomass power offers utilities a potential pathway to increase their renewable generation portfolios for compliance with renewable energy standards and to reduce greenhouse gas (GHG) emissions relative to current fossil-based technologies. To date, a large body of life-cycle assessment (LCA) literature assessing biopower’s life-cycle GHG emissions has been published.
Interest in using biomass feedstocks to produce power, liquid fuels, and chemicals in the U.S. is increasing. Central to determining the potential for these industries to develop is an understanding of the location, quantities, and prices of biomass resources. This paper describes the methodology used to estimate biomass quantities and prices for each state in the continental U.S. An Excel™ spreadsheet contains estimates of biomass quantities potentially available in five categories: mill wastes, urban wastes, forest residues, agricultural residues and energy crops.
National biomass feedstock assessments (Perlack et al., 2005; DOE, 2011) have focused on cellulosic biomass resources, and have not included potential algal feedstocks. Recent research (Wigmosta et al., 2011) provides spatially-‐explicit information on potential algal biomass and oil yields, water use, and facility locations. Oak Ridge National Laboratory and Pacific Northwest National Lab are collaborating to integrate terrestrial and algal feedstock resource assessments. This poster describes preliminary results of this research.
Algae feedstocks for alternative fuels production are not economically competitive with fossil fuels at the present time. Furthermore, it has not yet been demonstrated that algae production systems offer improved sustainability characteristics.
Provides a summary of the key findings of the IPCC Special Report on Renewable Energy Sources (SRREN) and Climate Change Mitigation.
The IPCC SRREN report addresses information needs of policymakers, the private sector and civil society on the potential of renewable energy sources for the mitigation of climate change, providing a comprehensive assessment of renewable energy technologies and related policy and financial instruments. The IPCC report was a multinational collaboration and synthesis of peer reviewed information: Reviewed, analyzed, coordinated, and integrated current high quality information.
Ethanol use in the U.S. rose sharply in recent years due to public policy and a spike in petroleum prices, and remains high. Public support for ethanol includes mandated minimum levels of use nationwide. However, rather little is known about consumer demand for ethanol and much less about demand by type of blend and ethanol source. We used trial survey data and conjoint analysis to overcome the lack of historical data on consumers’ preferences for ethanol blend fuels.
This paper examines the possibilities of breaking into the cellulosic ethanol market in south Louisiana via strategic feedstock choices and the leveraging of the area’s competitive advantages. A small plant strategy is devised whereby the first-mover problem might be solved, and several scenarios are tested using Net Present Value analysis.
This paper introduces a spatial bioeconomic model for study of potential cellulosic biomass supply at regional scale. By modeling the profitability of alternative crop production practices, it captures the opportunity cost of replacing current crops by cellulosic biomass crops. The model draws upon biophysical crop input-output coefficients, price and cost data, and spatial transportation costs in the context of profit maximization theory. Yields are simulated using temperature, precipitation and soil quality data with various commercial crops and potential new cellulosic biomass crops.
Events external to agriculture have set in motion the conditions for structural change in the marketing of corn in the U.S. These included a rapid increase in the price of crude oil from $40 per barrel to over $100 caused by hurricanes, geopolitical events, an increased global demand for energy from countries like China and India, and in December 2007, the U.S. raising the renewable fuel standards. The results of this research show that there could be significant changes in the historical utilization and marketing of corn in the U.S.
In this study we use data envelopment analysis to decompose the overall economic efficiency of a sample of ethanol plants into three subcomponents: technical efficiency, allocative efficiency and a new component we call marketing efficiency. The relative importance of these sources of efficiency is of particular interest given the recent history of bankruptcies, plant closings and ownership change in the industry. Results reveal that observed production units are very efficient from a technical point of view as suggested by a standard deviation of 1% in technical efficiency.