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.
The Biomass Scenario Model (BSM) is a system dynamics model that represents the entire biomass-to-biofuels supply chain, from feedstock to fuel use. It is a tool designed to better understand biofuels policy as it impacts the development of the supply chain for biofuels in the United States.
This page houses the BSM articles that have been published. For more information, see the link to NREL's list of publications on the BSM.
n the past decades, the production of biomass for energy in agriculture and forestry has increased in many parts of the world. For years to come, further increase in land use for bioenergy will be needed to meet the renewable energy ambitions of many countries, and to reduce fossil fuel use and associated GHG emissions.
A primary objective of current U.S. biofuel law – the “Energy Independence and Security Act of 2007” (EISA) – is to reduce dependence on imported oil, but the law also requires biofuels to meet carbon emission reduction thresholds relative to petroleum fuels. EISA created a renewable fuel standard with annual targets for U.S. biofuel use that climb gradually from 9 billion gallons per year in 2008 to 36 billion gallons (or about 136 billion liters) of biofuels per year by 2022. The most controversial aspects of U.S.
We quantify the emergence of biofuel markets and its impact on U.S. and world agriculture for the coming decade using the multi-market, multi-commodity international FAPRI (Food and Agricultural Policy Research Institute) model. The model incorporates the trade-offs between biofuel, feed, and food production and consumption and international feedback effects of the emergence through world commodity prices and trade.
In this paper we investigate the potential production and implications of a global biofuels industry. We develop alternative approaches to the introduction of land as an economic factor input, in value and physical terms, into a computable general equilibrium framework. Both approach allows us to parameterize biomass production in a manner consistent with agro-engineering information on yields and a ?second generation? cellulosic biomass conversion technology.
The preceding two chapters of this volume have discussed physical and economic data bases for global agriculture and forestry, respectively. These form the foundation for the integrated, global land use data base discussed in this chapter. However, in order to utilize these data for global CGE analysis, it is first necessary to integrate them into a global, general equilibrium data base. This integration is the subject of the present chapter
This paper describes the GTAP land use data base designed to support integrated assessments of the potential for greenhouse gas mitigation. It disaggregates land use by agro-ecological zone (AEZ). To do so, it draws upon global land cover data bases, as well as state-of-the-art definition of AEZs from the FAO and IIASA. Agro-ecological zoning segments a parcel of land into smaller units according to agro-ecological characteristics, including: precipitation, temperature, soil type, terrain conditions, etc. Each zone has a similar combination of constraints and potential for land use.
The paper describes the on-going project of the GTAP land use data base. We also present the GTAPE-AEZ model, which illustrates how land use and land-based emissions can be incorporated in the CGE framework for Integrated Assessment (IA) of climate change policies. We follow the FAO fashion of agro-ecological zoning (FAO, 2000; Fischer et al, 2002) to identify lands located in six zones. Lands located in a specific AEZ have similar (or homogenous) soil, landform and climatic characteristics.
It is technically feasible to capture CO2 from the flue gas of a coal-fired power plant and various researchers are working to understand the fate of sequestered CO2 and its long term environmental effects. Sequestering CO2 significantly reduces the CO2 emissions from the power plant itself, but this is not the total picture.
This report discusses the development of greenhouse gas (GHG) emissions estimates for the production of Fischer-Tropsch (FT) derived fuels (in particular, FT diesel), makes comparisons of these estimates to reported literature values for petroleum-derived diesel, and outlines strategies for substantially reducing these emissions.
Biodiesel is a renewable diesel fuel substitute. It can be made from a variety of natural oils and fats. Biodiesel is made by chemically combining any natural oil or fat with an alcohol such as methanol or ethanol. Methanol has been the most commonly used alcohol in the commercial production of biodiesel. In Europe, biodiesel is widely available in both its neat form (100% biodiesel, also know as B100) and in blends with petroleum diesel. European biodiesel is made predominantly from rapeseed oil (a cousin of canola oil).
Human actions are altering the terrestrial environment at unprecedented rates, magnitudes, and spatial scales. Landcover change stemming from human land uses represents a major source and a major element of global environmental change. Not only are the global-level data on landuse and land-cover change relatively poor, but we need a much better understanding of the underlying driving forces for these changes. Many forces have been proposed as significant, but single-factor explanations of land transformation have proved to be inadequate.
We present a system dynamics global LUC model intended to examine LUC attributed to biofuel production. The model has major global land system stocks and flows and can be exercised under different food and biofuel demand assumptions. This model provides insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy rather than a precise number generator.
The estimation of greenhouse gas (GHG) emissions from a change in land-use and management resulting from growing biofuel feedstocks has undergone extensive – and often contentious – scientific and policy debate. Emergent renewable fuel policies require life cycle GHG emission accounting that includes biofuel-induced global land-use change (LUC) GHG emissions. However, the science of LUC generally, and biofuels-induced LUC specifically, is nascent and underpinned with great uncertainty.
ABSTRACT: A growing number of countries are implementing greenhouse gas (GHG) emissions trading schemes. As these schemes impose a cost for GHG emissions they should increase the competitiveness of low carbon fuels. Bioenergy from biomass is regarded as carbon neutral in most of the schemes, therefore incurring no emission costs. Emissions trading schemes may therefore encourage increased use of biomass for energy, and under certain conditions may also incentivize the construction of new bioenergy plants.
Provides a summary of the key findings of the IPCC Special Report on Renewable Energy Sources (SRREN) and Climate Change Mitigation.
EXECUTIVE SUMMARY: Life cycle assessment (LCA) is a powerful tool that may be used to quantify the environmental impacts of products and services. It includes all processes, from cradle-to-grave, along the supply chain of the product. When analysing energy systems, greenhouse gas (GHG) emissions (primarily CO2, CH4 and N2O) are the impact of primary concern. In using LCA to determine the climate change mitigation benefits of bioenergy, the life cycle emissions of the bioenergy system are compared with the emissions for a reference energy system.
Despite a rapid worldwide expansion of the biofuel industry, there is a lack of consensus within the scientific community about the potential of biofuels to reduce reliance on petroleum and decrease greenhouse gas (GHG) emissions. Although life cycle assessment provides a means to quantify these potential benefits and environmental impacts, existing methods limit direct comparison within and between different biofuel systems because of inconsistencies in performance metrics, system boundaries, and underlying parameter values.