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.
KDF Search Results
Advanced biomass feedstocks tend to provide more non-fuel ecosystem goods and services (ES) than 1st-generation alternatives. We explore the idea that payment for non-fuel ES could facilitate market penetration of advanced biofuels by closing the profitability gap. As a specific example, we discuss the Mississippi-Atchafalaya River Basin (MARB), where 1st-generation bioenergy feedstocks (e.g., corn-grain) have been integrated into the agricultural landscape.
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.
Reducing dependence on fossil‐based energy has raised interest in biofuels as a potential energy source, but concerns have been raised about potential implications for water quality. These effects may vary regionally depending on the biomass feedstocks and changes in land management. Here, we focused on the Tennessee River Basin (TRB), USA.
This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply.