">

Documentation for the Calculating Uncertainty in Biomass Emissions Model, Version 1.0 (CUBE 1.0)

Contents and Use

Aimee E. Curtright, Henry H. Willis, David R. Johnson, David S. Ortiz, Nicholas E. Burger, Constantine Samaras

ResearchPosted on rand.org 2010Published in: Documentation for the Calculating Uncertainty in Biomass Emissions Model, Version 1.0 (CUBE 1.0): Contents and Use (Washington, D.C.: U.S. Dept. of Energy, 2010), 73 p

The Calculating Uncertainty in Biomass Emissions (CUBE) model is a tool to estimate GHG emissions from the cultivation, preparation, and delivery of biomass feedstocks (i.e., "farm-to-gate" emissions) for energy production and the uncertainty in these emissions. Version 1.0 of the model estimates farm-to-gate emissions of three dedicated energy crops (corn grain, switchgrass, and mixed prairie biomass) and two biomass residues (forest residue and mill residue). CUBE 1.0 is publicly available through NETL's Web site. Documentation of source literature and default parameter values is provided in the model itself. An overview of the model structure and use is also available in the model documentation report. This document complements the information contained in the model by (1) describing how users can navigate and find information in the model; (2) providing an overview of the structure of the model; and (3) describing the variables and equations contained in the model. The model was developed using Analytica and can be used with the free Analytica player.

Topics

Document Details

  • Publisher: National Energy Technology Laboratory
  • Availability: Non-RAND
  • Year: 2010
  • Pages: 66
  • Document Number: EP-201013-03

This publication is part of the RAND external publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.