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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This is a joint report between three national labs, ORNL, INL, and ANL, that describes outcomes from a workshop. The Bioenergy Solutions to Gulf Hypoxia Workshop gathered stakeholders from industry, academia, national laboratories, and U.S. federal agencies to discuss how biomass feedstocks could help decrease nutrient loadings to the Gulf of Mexico (Gulf), a root cause of the large hypoxic zone that forms each summer.
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.
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
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
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