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.
There is an inextricable link between energy production and food/feed/fiber cultivation with available water resources. Currently in the United States, agriculture represents the largest sector of consumptivewater usemaking up 80.7%of the total. Electricity generation in the U.S. is projected to increase by 24 % in the next two decades and globally, the production of liquid transportation fuels are forecasted to triple over the next 25-years, having significant impacts on the import/export market and global economies.
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.
This paper describes the development of a set of U.S. county-based vehicle miles of travel and motor fuel use estimates and forecasts. The forecasts are short range, annual forecasts out to year 2015. A range of forecasts can be generated based on different assumptions associated with household travel growth and alternative fuel use scenarios.
This model was developed at Idaho National Laboratory and focuses on crop production. This model is an agricultural cultivation and production model, but can be used to estimate biomass crop yields.
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.
Increasing demand for crop-based biofuels, in addition to other human drivers of land use, induces direct and indirect land use changes (LUC). Our system dynamics tool is intended to complement existing LUC modeling approaches and to improve the understanding of global LUC drivers and dynamics by allowing examination of global LUC under diverse scenarios and varying model assumptions. We report on a small subset of such analyses.
Provides a summary of the key findings of the IPCC Special Report on Renewable Energy Sources (SRREN) and Climate Change Mitigation.
Biofuels are presented in rich countries as a solution to two crises: the climate crisis and the oil crisis. But they may not be a solution to either, and instead are contributing to a third: the current food crisis.
Crop intensification is often thought to increase greenhouse gas (GHG) emissions, but studies in which crop management is optimized to exploit crop yield potential are rare. We conducted a field study in eastern Nebraska, USA to quantify GHG emissions, changes in soil organic carbon (SOC) and the net global warming potential (GWP) in four irrigated systems: continuous maize with recommended best management practices (CC-rec) or intensive management (CC-int) and maize–soybean rotation with recommended (CS-rec) or intensive management (CS-int).
The IPCC SRREN report addresses information needs of policymakers, the private sector and civil society on the potential of renewable energy sources for the mitigation of climate change, providing a comprehensive assessment of renewable energy technologies and related policy and financial instruments. The IPCC report was a multinational collaboration and synthesis of peer reviewed information: Reviewed, analyzed, coordinated, and integrated current high quality information.
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. The data products include population count grids (raw counts), population density grids (per square km), land area grids (actual area net of ice and water), mean administrative unit area grids, centroids, a national identifier grid, national boundaries, and coastlines.
The Global Rural-Urban Mapping Project (GRUMP), Alpha Version consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. The data products include population count grids (raw counts), population density grids (per square km), land area grids (actual area net of ice and water), mean geographic unit area grids, urban extents grids, centroids, a national identifier grid, national boundaries, coastlines, and settlement points.
USDA Agricultural Projections for 2011-20, released in February 2011, provide longrun projections for the farm sector for the next 10 years. These annual projections cover agricultural commodities, agricultural trade, and aggregate indicators of the sector, such as farm income and food prices.
Important assumptions for the projections include:
PEATSim (Partial Equilibrium Agricultural Trade Simulation) is a dynamic, partial equilibrium, mathematical-based model that enables users to reach analytical solutions to problems, given a set of parameters, data, and initial
conditions. This theoretical tool developed by ERS incorporates a wide range of domestic and border policies that enables it to estimate the market and trade effects of policy changes on agricultural markets. PEATSim captures
Agricultural markets often feature significant transport costs and spatially distributed production and processing which causes spatial imperfect competition. Spatial economics considers the firms’ decisions regarding location and spatial price strategy separately, usually on the demand side, and under restrictive assumptions. Therefore, alternative approaches are needed to explain, e.g., the location of new ethanol plants in the U.S. at peripheral as well as at central locations and the observation of different spatial price strategies in the market.
This database contains current and historical official USDA data on production, supply and distribution of agricultural commodities for the United States and key producing and consuming countries.