Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level.
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Negative environmental consequences of fossil fuels and concerns about petroleum supplies have spurred the search for renewable transportation biofuels. To be a viable alternative, a biofuel should provide a net energy gain, have environmental benefits, be economically competitive, and be producible in large quantities without reducing food supplies. We use these criteria to evaluate, through life-cycle accounting, ethanol from corn grain and biodiesel from soybeans. Ethanol yields 25% more energy than the energy invested in its production, whereas biodiesel yields 93% more.
The standard GTAP framework is documented in Global Trade Analysis: Modeling and Applications, T.W. Hertel (ed.), published in 1997 by Cambridge University Press.
This book is divided into 4 parts:
Introduction
Model structure, Data Base, and software
Selected applications
Evaluation of the framework
Developed at IFPRI in 1990s, upon the realization that there was a lack of long-term vision and consensus among policy makers and researchers about the actions that are necessary to feed the world in the future, reduce poverty, and protect the natural resource base. This paper provides an updated description of the methodology for IMPACT.
CAPRI is a success story of an economic model developed by European Commission research funds. Operational since almost a decade, it supports decision making related to the Common Agricultural Policy based on sound scientific quantitative analysis. CAPRI is only viable due to its Pan-European network of researchers which based on an open source approach tender together for projects, develop and maintain the model, apply it for policy impact assessment, write scientific publications and consult clients based on its results.
The Targets IMage Energy Regional (TIMER) Model was developed and used in close connection with the Integrated Model to Assess the Global Environment (IMAGE) 2.2. The system-dynamics TIMER model simulates the global energy system at an intermediate level of aggregation.
A environmental model for assessing impacts of policy on climate, land and the environment.
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.
We highlight the complexity of land-use/cover change and propose a framework for a more general understanding of the issue, with emphasis on tropical regions. The review summarizes recent estimates on changes in cropland, agricultural intensification, tropical deforestation, pasture expansion, and urbanization and identifies the still unmeasured land-cover changes. Climate-driven land-cover modifications interact with land-use changes.
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.
Greenhouse gas release from land use change (the socalled ?carbon debt?) has been identified as a potentially significant contributor to the environmental profile of biofuels. The time required for biofuels to overcome this carbon debt duetolandusechangeandbeginprovidingcumulativegreenhouse gas benefits is referred to as the ?payback period? and has been estimated to be 100-1000 years depending on the specific ecosystem involved in the land use change event. Two mechanisms for land use change exist: ?direct?
The different versions of the CLUE model (CLUE, CLUE-CR, CLUE-s, Dyna-CLUE and CLUE-Scanner) are among the most frequently used land use models globally. Applications range from small regions to entire continents. The CLUE model is a flexible, generic land use modeling framework which allows scale and context specific specification for regional applications.
The actual land use consequences of crop consumption are not very well reflected in existing life cycle inventories. The state of the art is that such inventories typically include data from crop production in the country in which the crop is produced, and consequently the inventories do not necessarily consider the land ultimately affected in the systems being studied.
Ground-based data on crop production in the USA is provided through surveys conducted by the National Agricultural Statistics Service (NASS) and the Census of Agriculture (AgCensus). Statistics from these surveys are widely used in economic analyses, policy design, and for other purposes. However, missing data in the surveys presents limitations for research that requires comprehensive data for spatial analyses.We created comprehensive county-level databases for nine major crops of the USA for a 16-yr period, by filling the gaps in existing data reported by NASS and AgCensus.
The Energy-Economy-Environment Modelling Laboratory E3MLab operating within the Institute of Communication and Computer Systems of the National Technical University of Athens (ICCS/NTUA), Department of Electrical and Computer Engineering, is a laboratory that specializes in the construction and use of large scale computerised models covering the areas of Energy, the Economy and the Environment. Such models are used to make projections and analyse complex issues requiring system-wide consideration. Special emphasis is given to policy analysis and support.
Two of the most widely used land-cover data sets for the United States are the National Land-Cover Data (NLCD) at 30-m resolution and the Global Land- Cover Characteristics (GLCC) at 1-km nominal resolution. Both data sets were produced around 1992 and expected to provide similar land-cover information. This study investigated the spatial distribution of NLCD within major GLCC classes at 1-km unit over a total of 11 agricultural-related eco-regions across the continental United States.
Increasing energy use, climate change, and carbon dioxide (CO2) emissions from fossil fuels make switching to lowcarbon fuels a high priority. Biofuels are a potential lowcarbon energy source, but whether biofuels offer carbon savings depends on how they are produced. Converting rainforests, peatlands, savannas, or grasslands to produce food-based biofuels in Brazil, Southeast Asia, and the United States creates a ?biofuel carbon debt? by releasing 17 to 420 times more CO2 than the annual greenhouse gas (GHG) reductions these biofuels provide by displacing fossil fuels.
For several years the Idaho National Laboratory (INL) has been developing a Decision Support System for Agriculture (DSS4Ag) which determines the economically optimum recipe of various fertilizers to apply at each site in a field to produce a crop, based on the existing soil fertility at each site, as well as historic production information and current prices of fertilizers and the forecast market price of the crop at harvest.
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.
IBSAL is a dynamic simulation model of the connections existing between feedstock producers, biorefinery locations and the requisite storage and distribution systems. The model is primarily focused on the front end of the biofuels supply chain at the local level. The local data sources that are inputs include field area, dry matter, production equipment, soil and biomass moisture, weather conditions, transportation networks and associated costs. The model was developed at Oak Ridge National Laboratory.
This model can be downloaded from