KDF Search Results

Abstract

The U.S. Department of Energy’s (DOE’s) Co-Optimization (Co-Optima) initiative is accelerating the introduction of affordable, scalable, and sustainable fuels and high-efficiency, low-emission engines with a first-of-its-kind effort to simultaneously tackle fuel and engine research and development (R&D).

Abstract: Cellulosic-based biofuels are needed to help meet energy needs and to strengthen rural investment and development in the midwestern United States (US). This analysis identifies 11 categories of indicators to measure progress toward sustainability that should be monitored to determine if ecosystem and social services are being maintained, enhanced, or disrupted by production, harvest, storage, and transport of cellulosic feedstock.

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.

There is an inextricable link between energy production and food/feed/fiber cultivation with available water resources. Currently in the United States, agriculture represents the largest sector of consumptivewater usemaking up 80.7%of the total. Electricity generation in the U.S. is projected to increase by 24 % in the next two decades and globally, the production of liquid transportation fuels are forecasted to triple over the next 25-years, having significant impacts on the import/export market and global economies.

Excess nutrients from agriculture in the Mississippi River drainage, USA have degraded water quality in
freshwaters and contributed to anoxic conditions in downstream estuaries. Consequently, water quality is a
significant concern associated with conversion of lands to bioenergy production. This study focused on the
Arkansas-White-Red river basin (AWR), one of five major river basins draining to the Mississippi River. The
AWR has a strong precipitation gradient from east to west, and advanced cellulosic feedstocks are projected to

A framework for selecting and evaluating indicators of bioenergy sustainability is presented.
This framework is designed to facilitate decision-making about which indicators are useful for assessing
sustainability of bioenergy systems and supporting their deployment. Efforts to develop sustainability
indicators in the United States and Europe are reviewed. The fi rst steps of the framework for
indicator selection are defi ning the sustainability goals and other goals for a bioenergy project or program,

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.

Agroecosystem models that can incorporate management practices and quantify environmental effects
are necessary to assess sustainability-associated food and bioenergy production across spatial scales.
However, most agroecosystem models are designed for a plot scale. Tremendous computational capacity
on simulations and datasets is needed when large scales of high-resolution spatial simulations are conducted.
We used the message passing interface (MPI) parallel technique and developed a master–slave

In order to aid operations that promote sustainability goals, researchers and stakeholders use sustainability assessments.  Although assessments take various forms, many utilize diverse sets of indicators numbering anywhere from two to over 2000. Indices, composite indicators, or aggregate values are used to simplify high dimensional and complex data sets and to clarify assessment results. Although the choice of aggregation function is a key component in the development of the assessment, there are fewliterature examples to guide appropriate

Landscape design provides an approach under which bioenergy production systems can be integrated into other components of the land, environment and socioeconomic system. Landscape design is a spatially explicit collaborative plan for resource allocation and management. It should be applied to a particular area and developed with the involvement of key stakeholders.

Potential global biodiversity impacts from near-term gasoline production are compared to biofuel, a renewable liquid transportation fuel expected to substitute for gasoline in the near term (i.e., from now until c.

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.

Water sustainability is an integral part of the environmental sustainability. Water use, water quality, and the demand on water resource for bioenergy production can have potential impacts to food, feed, and fiber production and to our social well-being. With the support from United State Department of Energy, Argonne National Laboratory is developing a life cycle water use assessment tool for biofuels production at the national scale with multiple spatial resolutions.

The sustainability of future bioenergy production rests on more than continual improvements in its environmental, economic, and social impacts. The emergence of new biomass feedstocks, an expanding array of conversion pathways, and expected increases in overall bioenergy production are connecting diverse technical, social, and policy communities. These stakeholder groups have different—and potentially conflicting—values and cultures, and therefore different goals and decision making processes. Our aim is to discuss the implications of this diversity for bioenergy researchers.

Indicators of the environmental sustainability of biofuel production, distribution, and use should be selected, measured, and interpreted with respect to the context in which they are used. The context of a sustainability assessment includes the purpose, the particular biofuel production and distribution system, policy conditions, stakeholder values, location, temporal influences, spatial scale, baselines, and reference scenarios.

The production of biobased feedstocks (i.e., plant– or algal-based material use for transportation fuels, heat, power and bioproducts) for energy consumption has been expanding rapidly in recent years. Biomass now accounts for 4.1% of total U.S. primary energy production. Unfortunately, there are considerable knowledge gaps relative to implications of this industry expansion for wildlife.

Indicators are needed to assess environmental sustainability of bioenergy systems. Effective indicators
will help in the quantification of benefits and costs of bioenergy options and resource uses. We identify
19 measurable indicators for soil quality, water quality and quantity, greenhouse gases, biodiversity, air
quality, and productivity, building on existing knowledge and on national and international programs
that are seeking ways to assess sustainable bioenergy. Together, this suite of indicators is hypothesized

Landscape ecology focuses on the spatial patterns and processes of ecological and human interactions. These patterns and processes are being altered by both changing resource-management practices of humans and changing climate conditions associated, in part, with increases in atmospheric concentrations of greenhouse gases. Dominant resource-extraction and land-management activities involve energy, and the use of fossil energy is one of the key drivers behind increasing greenhouse gas emissions as well as land-use changes.

Land-use change (LUC) estimated by economic models has sparked intense international debate. Models estimate how much LUC might be induced under prescribed scenarios and rely on assumptions to generate LUC values. It is critical to test and validate underlying