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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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.
Join the U.S. Department of Energy’s Bioenergy Technologies Office on Dec. 6, 2018, at 1 p.m. CST for a webinar on “Biomass Production and Water Quality in the Mississippi River Basin.” In this webinar, Argonne National Laboratory and Oak Ridge National Laboratory will jointly present modeling and analyses of potential implications of biomass production on nutrients and sediments in each of the six tributaries of the Mississippi River Basin.
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.
Synthesis manuscript for an Ecology & Society Special Feature on Telecoupling: A New Frontier for Global Sustainability
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