Logging and mill residues are currently the largest sources of woody biomass for bioenergy in the US, but short-rotation woody crops (SRWCs) are expected to become a larger contributor to biomass production, primarily on lands marginal for food production. However, there are very few studies on the environmental effects of SRWCs, and most have been conducted at stand rather than at watershed scales.
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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.
Link to the website with documentation and download instructions for the PNNL Global Change Assessment Model (GCAM), a community model or long-term, global energy, agriculture, land use, and emissions. BioEnergy production, transformation, and use is an integral part of GCAM modeling and scenarios.
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.
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