The objective of this research project was to assess whether standard forestry best management practices (BMPs) are sufficient to protect stream water quality from intensive silviculture associated with short-rotation woody crop (SRWC) production for bioenergy. Forestry BMPs are designed to prevent the movement of deleterious quantities of nutrients, herbicides, sediments, and thermal energy (sunlight hitting stream channels) from clear-cuts and plantations to surface waters.
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Model-data comparisons are always challenging, especially when working at a large spatial scale and evaluating multiple response variables. We implemented the Soil and Water Assessment Tool (SWAT) to simulate water quantity and quality for the Tennessee River Basin.
With the goal of understanding environmental effects of a growing bioeconomy, the U.S. Department of Energy (DOE), national laboratories, and U.S. Forest Service research laboratories, together with academic and industry collaborators, undertook a study to estimate environmental effects of potential biomass production scenarios in the United States, with an emphasis on agricultural and forest biomass. Potential effects investigated include changes in soil organic carbon (SOC), greenhouse gas (GHG) emissions, water quality and quantity, air emissions, and biodiversity.
This dataset reports the pre-treatment hydrology and pre- and post-treatment water quality data from a watershed-scale experiment that is evaluating the effects of growing short-rotation loblolly pine for bioenergy on water quality and quantity in the southeastern U.S. The experiment is taking place on the Savannah River Site, near New Ellenton, South Carolina, USA. Beginning in 2010, water quality and hydrology were measured for two years in 3 watersheds (R, B, C).
One approach to assessing progress towards sustainability makes use of multiple indicators spanning the
environmental, social, and economic dimensions of the system being studied. Diverse indicators have different
units of measurement, and normalization is the procedure employed to transform differing indicator
measures onto similar scales or to unit-free measures. Given the inherent complexity entailed in interpreting
information related to multiple indicators, normalization and aggregation of sustainability indicators
The Federal Activities Report on the Bioeconomy has been prepared to emphasize the significant potential for an even stronger U.S. bioeconomy through the production and use of biofuels, bioproducts, and biopower. Bioeconomy activities have already touched on the interests of many federal agencies and offices. This report is intended to educate the public on the wide-ranging, federally funded activities that are helping to bolster the bioeconomy.
Conventional feedstock supply systems exist and have been developed for traditional agriculture and forestry systems. These conventional feedstock supply systems can be effective in high biomass-yielding areas (such as for corn stover in Iowa and plantation-grown pine trees in the southern United States), but they have their limits, particularly with respect to addressing feedstock quality and reducing feedstock supply risk to biorefineries. They also are limited in their ability to efficiently deliver energy crops.
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
Understanding the development of the biofuels industry in the United States is important to policymakers and industry. The Biomass Scenario Model (BSM) is a system dynamics model of the biomass-to-biofuels system that can be used to explore policy effects on biofuels development. Because of the complexity of the model, as well as the wide range of possible future conditions that affect biofuels industry development, we have not developed a single reference case but instead developed a set of specific scenarios that provide various contexts for our analyses.
The Biomass Scenario Model (BSM) is a system dynamics model that represents the entire biomass-to-biofuels supply chain, from feedstock to fuel use. The BSM is a complex model that has been used for extensive analyses; the model and its results can be better understood if input data used for initialization and calibration are well-characterized. It has been carefully validated and calibrated against the available data, with data gaps filled in using expert opinion and internally consistent assumed values.