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.
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.
Agricultural activities have dramatically altered our planet?s land surface. To understand the extent and spatial distribution of these changes, we have developed a new global data set of croplands and pastures circa 2000 by combining agricultural inventory data and satellite-derived land cover data. The agricultural inventory data, with much greater spatial detail than previously available, is used to train a land cover classification data set obtained by merging two different satellite-derived products (Boston University?s MODIS-derived land cover product and the GLC2000 data set).
Growing concern about climate change and energy security has led to increasing interest in developing renewable, domestic energy sources for meeting electricity, heating and fuel needs in the United States. Illinois has significant potential to produce bioenergy crops, including corn, soybeans, miscanthus (Miscanthus giganteus), and switchgrass (Panicum virgatum). However, land requirements for bioenergy crops place them in competition with more traditional agricultural uses, in particular food production.
Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution.
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.
Provides a summary of the key findings of the IPCC Special Report on Renewable Energy Sources (SRREN) and Climate Change Mitigation.
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.
Traffic flows in the U.S. have been affected by the substantial increase and, as of January 2009, decrease in biofuel production and use. This paper considers a framework to study the effect on grain transportation flows of the 2005 Energy Act and subsequent legislation, which mandated higher production levels of biofuels, e.g. ethanol and biodiesels. Future research will incorporate changes due to the recent economic slowdown.
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.
The most frequently used climate classification map is that ofWladimir Köppen, presented in its latest version
1961 by Rudolf Geiger. A huge number of climate studies and subsequent publications adopted this or a
former release of the Köppen-Geiger map. While the climate classification concept has been widely applied
to a broad range of topics in climate and climate change research as well as in physical geography, hydrology,
agriculture, biology and educational aspects, a well-documented update of the world climate classification
In a previous paper we presented an update of the highly referenced climate classification map, that of Wladimir Koppen, which was published for the first time in 1900 and updated in its latest version by Rudolf Geiger in 1961. This updated world map of Koppen-Geiger climate classification was based on temperature and precipitation observations for the period 1951–2000.
Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends.
When fuelwood is harvested at a rate exceeding natural growth and inefficient conversion technologies are used, negative environmental and socio-economic impacts, such as fuelwood shortages, natural forests degradation and net GHG emissions arise. In this study, we argue that analyzing fuelwood supply/demand spatial patterns require multiscale approaches to effectively bridge the gap between national results with local situations.
This paper describes a methodology to explore the (future) spatial distribution of biofuel crops in Europe. Two main types of biofuel crops are distinguished: biofuel crops used for the production of biodiesel or bioethanol, and second-generation biofuel crops. A multiscale, multi-model approach is used in which biofuel crops are allocated over the period 2000?2030. The area of biofuel crops at the national level is determined by a macroeconomic model. A spatially explicit land use model is used to allocate the biofuel crops within the countries.