KDF Search Results

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.

The framework for National Algal Biofuels Technology Roadmap was constructed at the Algal Biofuels Technology Roadmap Workshop, held December 9-10, 2008, at the University of Maryland-College Park. The Workshop was organized by the Biomass Program to discuss and identify the critical challenges currently hindering the development of a domestic, commercial-scale algal biofuels industry. This Roadmap presents information from a scientific, economic, and policy perspectives that can support and guide RD&D investment in algal biofuels.

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

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).

Growing concern about climate change and energy security has led to increasing interest in developing renewable, domestic energy sources for meeting electricity, heating and fuel needs in the United States. Illinois has significant potential to produce bioenergy crops, including corn, soybeans, miscanthus (Miscanthus giganteus), and switchgrass (Panicum virgatum). However, land requirements for bioenergy crops place them in competition with more traditional agricultural uses, in particular food production.

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.

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.

In 2013 a series of meetings was held across the US with each of the Sun Grant Regional Feedstock Partnership crop teams and the resource assessment team, led by the Oregon State University and Oak Ridge National Laboratory, to review, standardize, and verify energy crop yield trials from 2007-2012 and assimilate their outcomes into a national model of biomass yield suitability.

This document provides presentation style maps of potential crop yield of dedicated bioenergy crops from the publication "Productivity Potential of Bioenergy Crops from the Sun Grant Regional Feedstock Partnership." 2013. Eaton, Laurence, Chris Daly, Mike Halbleib, Vance Owens, Bryce Stokes. ORNL/TM-2013/574.

The European Bioinformatics Institute - algae whole genome record - cyanobacteria.

NCBI: http://www.ncbi.nlm.nih.gov/nuccore/AP008231

National Centers for Coastal Ocean Science (NCCOS) has published the availability of funds and Announcements of Opportunity for the competitive programs.

The Monitoring and Event Response for Harmful Algal Blooms (MERHAB) Research Program builds capacity along our coasts for enhanced HAB monitoring and response. This helps NOAA and state partners identify when beaches, shellfisheries, and marine animals are at risk from harmful algae, and to make informed decisions that protect public health and safeguard our coastal economies.

NOAA and other federal agencies administer a variety of financial assistance programs that support sustainable aquaculture in the United States. Funding may address a variety of issues such as environmental monitoring, recirculating aquaculture systems, shellfish farming, alternative feeds for aquaculture, new species research, and offshore aquaculture. The programs below outline NOAA-managed funding opportunities for aquaculture and funding opportunities available through other agencies or venues.

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.

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.

Switchgrass (Panicum virgatum L.) is a perennial grass native to the United States that has been studied as a sustainable source of biomass fuel. Although many field-scale studies have examined the potential of this grass as a bioenergy crop, these studies have not been integrated. In this study, we present an empirical model for switchgrass yield and use this model to predict yield for the conterminous United States. We added environmental covariates to assembled yield data from field trials based on geographic location. We developed empirical models based on these data.

Traffic flows in the U.S. have been affected by the substantial increase and, as of January 2009, decrease in biofuel production and use. This paper considers a framework to study the effect on grain transportation flows of the 2005 Energy Act and subsequent legislation, which mandated higher production levels of biofuels, e.g. ethanol and biodiesels. Future research will incorporate changes due to the recent economic slowdown.

Agricultural markets often feature significant transport costs and spatially distributed production and processing which causes spatial imperfect competition. Spatial economics considers the firms’ decisions regarding location and spatial price strategy separately, usually on the demand side, and under restrictive assumptions. Therefore, alternative approaches are needed to explain, e.g., the location of new ethanol plants in the U.S. at peripheral as well as at central locations and the observation of different spatial price strategies in the market.