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This page provides information on models -- software programs and other tools -- used to analyze or predict the impacts of biofuels.

As the usage of biofuels -- and demand for feedstocks used in their production -- grows, changes are to be expected in terms of land use patterns, total greenhouse gases emitted, etc. Different models are therefore used by researchers and policymakers to assess land use changes, the life cycle impacts of biofuel use on greenhouse gas emissions, and other impacts on the economy, agriculture and the environment. Other models are used to assess the logistics of biofuels production and usage in the marketplace (such as supply chain-related models).

Below, various models are introduced, grouped by category. Where possible, descriptions of the models are given, along with information on the institutions that have developed each model.

Contents

Events

Land Use Change

Global

Regional

Life cycle analysis (LCA)/GHG emissions models

Click here for general information on life cycle analysis.

General

  • GaBi
    • PE International, Germany
    • Gabi Software includes several different versions such as GaBi 4, GaBi lite, GaBi DfX, and GaBi-EDIP and includes a huge range of databases . The models are capable of integrating and manipulating complex environmental factors to, for example, follow the life cycle of a product or service. The software is deemed a reliable and comprehensive tool to communicate life cycle assessment with internal and external constituents.
  • OpenLCA (Life Cycle Assessment)
    • Consortium, Germany
    • "The openLCA project will create, in the coming 1.5 years, a modular software for life cycle analysis and sustainability assessments. The software will be available as open source, and will be available for free." [3]

Fuel/Vehicle Models

  • A Lifecycle Emissions Model (LEM) (PDF file)
    • Guihua Wang and Mark Delucchi, UC Davis
    • LEM assesses energy and transportation lifecycles which represents fuel, vehicles, materials and infrastructure, to estimate CO2-equivalent greenhouse gas emissions, energy use and critera pollutant emissions.

For corn:

Click here for RSB Working Group on Greenhouse Gases

Economic

Global

Regional

  • Forest and Agricultural Sector Optimization Model (FASOM)
    • FASOM-GHG (PDF file)
    • EPA and Texas A&M (Bruce McCarl)
    • Collaborating Labs: ORNL and PNNL
    • Description

Agriculture/Environment

Examples:

  • CENTURY Model
    • Colorado State University
    • "The CENTURY version 5 agroecosystem model is the latest version of the soil organic model developed by Parton et al. (1987). This model simulates C, N, P, and S dynamics through an annual cycle over time scales of centuries and millennia. The producer submodel may be a grassland/crop, forest or savanna system, with the flexibility of specifying potential primary production curves representing the site-specific plant community. CENTURY was especially developed to deal with a wide range of cropping system rotations and tillage practices for system analysis of the effects of management and global change on productivity and sustainability of agroecosystems." (Source: Abstract from Oak Ridge National laboratory website.)
  • I_FARM Model
    • Iowa State University
    • "I-FARM is a database-driven farming systems simulation model that predicts economic returns and ecosystem impacts of farm operations, integrating both crop and livestock components. I-FARM was developed by Iowa State University to provide free access to farmers and decision makers....I-FARM focuses on agro-ecosystems in the United States....The model offers the selection of a range of crops and crop rotations, with the associated practices as tillage, fertilization, planting, weed control, harvesting, and residue removal. Livestock production is modeled based on feed intake, growth rate, grazing or confinement options, and manure management systems."[7]
  • SPARROW
    • United States Geological Survey (USGS)
    • "The SPARROW method uses spatially referenced regressions of contaminant transport on watershed attributes to support regional water-quality assessment goals, including descriptions of spatial and temporal patterns in water quality and identification of the factors and processes that influence those conditions. The method is designed to reduce the problems of data interpretation caused by sparse sampling, network bias, and basin heterogeneity." (Source: Abstract from the Goddard Space Flight Center website.)

Supply Chain/Infrastructure/Logistics

Examples:

  • Integrated Biomass Supply Analysis and Logistics (IBSAL) (PDF file)
    • Oak Ridge National Laboratory
    • "The IBSAL model is a simulation of a biomass supply chain. It consists of a network of operational modules and connectors threading the modules into a complete supply chain. Each module represents a process or an event. For example, grain combining, swathing, baling, loading a truck, truck travel, stacking, grinding, sizing, storing, each process is a module. Modules may also be processes such as drying, wetting, and chemical reactions such as breakdown of carbohydrates." [8]
  • Biomass Scenario Model (BSM)
    • National Renewable Energy Laboratory (NREL)
    • "The BSM is a dynamic model describing the deployment of biofuels technology in the marketplace. This model tracks the deployment of ethanol given development of new technologies (in feedstock collection, conversion and vehicles) and the reaction of the investment community to those technologies in light of the competing oil market, vehicle demand for biofuels and various government policies over time." (Source: CITATION NEEDED)

News

  • New Wikileaks show biofuel food impacts were underestimated, 14 December 2010 by Kenneth Richter of Friends of the Earth UK: "I found out today that biofuels and GM crops now have their very own Wikileak."
    • "The secret cables reveal some yet more evidence about US attempts to push GM crops onto Africa. The cables also contain notes from an international meeting called by Gordon Brown on biofuels and the food crises in 2008."
    • "In that meeting Joachim Von Braun, Director General of the [International] Food Policy Institute Research (IFPRI) suggested a moratorium on maize for biofuels. Their modelling showed it would immediately slash maize prices by 20 per cent and wheat prices by 10 per cent, with further reductions because it would discourage speculation."
    • "But this idea was dismissed by other participants. Cargill's Ruth Rawling predicted that wheat prices would come down quite quickly without the moratorium. The Overseas Development Institute estimated that prices would fall back from their 2008 peak to roughly what they had been in the early 1990s."
    • "How wrong they were."[9]
  • A wiki for the biofuels research community, 29 October 2010 by PhysOrg.com: "Researchers at the U.S. Department of Energy's Joint BioEnergy Institute (JBEI) have created a technoeconomic model that should help accelerate the development of a next generation of...biofuels....This on-line, wiki-based model enables researchers to pursue the most promising strategies for cost-efficient biorefinery operations by simulating such critical factors as production costs and energy balances under different processing scenarios."
    • "'The high production cost of biofuels has been the main factor limiting their widespread adoption,' says JBEI's Daniel Klein-Marcuschamer. 'We felt that a model of the biorefinery operation that was open, transparent about the assumptions it uses, and updatable by the community of users could aid in guiding research in the direction where it is most likely to reduce the production cost of biofuels.'"
    • "Klein-Marcuschamer, a post-doctoral researcher in JBEI's Deconstruction Division, was the lead author of a paper describing this research that was published in the journal Biomass and Bioenergy. The paper is titled "Technoeconomic analysis of biofuels: A wiki-based platform for lignocellulosic biorefineries (PDF file).'"
    • "The initial JBEI technoeconomic model is formulated to simulate a lignocellulosic ethanol biorefinery that uses corn stover feedstock. Model input factors include the cost of transporting the stover to a refinery, the use of acid pre-treatments to break down lignin and enzymes to break down cellulose into simples sugars, and the fermentation of these simple sugars into ethanol using yeast. From such inputs, users can calculate the resulting energy and greenhouse gas output."[10]



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