A key aspect in modeling the (future) competition between biofuels is the way in which production cost developments are computed. The objective of this study was threefold: (i) to construct a (endogenous) relation between cost development and cumulative production (ii) to implement technological learning based on both engineering study insights and an experience curve approach, and (iii) to investigate the impact of different technological learning assumptions on the market diffusion patterns of different biofuels.
KDF Search Results
Production of ethanol from agriculutural and forestry residues, municipal solid waste, energy crops, and other forms of lignocellulosic biomass could improve energy security, reduce trade deficits, decrease urban air pollution, and contribute little, if any, net carbon dioxide accumulation to the atmosphere. Dilute acid can open up the biomass structure for subsequent processing. The simultaneous saccharification and fermentation (SSF) process is favored for producing ethanol from the major fraction of lignocellulosic biomass, cellulose, because of its low cost potential.
The important key technologies required for the successful biological conversion of lignocellulosic biomass to ethanol have been extensively reviewed. The biological process of ethanol fuel production utilizing lignocellulose as substrate requires: (1) delignification to liberate cellulose and hemicellulose from their complex with lignin, (2) depolymerization of the carbohydrate polymers (cellulose and hemicellulose) to produce free sugars, and (3) fermentation of mixed hexose and pentose sugars to produce ethanol.
The rapidly expanding biofuel industry has changed the fundamentals of U.S. agricultural commodity markets. Increasing ethanol and biodiesel production has generated a fast-growing demand for corn and soybean products, which competes with the well-established domestic livestock industry and foreign buyers. Meanwhile, the co-products of biofuel production are replacing or displacing coarse grains and oilseed meal in feed rations for livestock.
Prior studies have estimated that a liter of bioethanol requires 263−784 L of water from corn farm to fuel pump, but these estimates have failed to account for the widely varied regional irrigation practices. By using regional time-series agricultural and ethanol production data in the U.S., this paper estimates the state-level field-to-pump water requirement of bioethanol across the nation. The results indicate that bioethanol’s water requirements can range from 5 to 2138 L per liter of ethanol depending on regional irrigation practices.
There is a strong societal need to evaluate and understand the sustainability of biofuels, especially because of the significant increases in production mandated by many countries, including the United States. Sustainability will be a strong factor in the regulatory environment and investments in biofuels. Biomass feedstock production is an important contributor to environmental, social, and economic impacts from biofuels.
The water consumption and agrochemical use during biofuel production could adversely impact both availability and quality of a precious resource.
In this paper, we assess what is known or anticipated about environmental and sustainability factors associated with next-generation biofuels relative to the primary conventional biofuels (i.e., corn grain-based ethanol and soybean-based diesel) in the United States during feedstock production and conversion processes. Factors considered include greenhouse (GHG) emissions, air pollutant emissions, soil health and quality, water use and water quality, wastewater and solid waste streams, and biodiversity and land-use changes.
Supply chain management involves all of the activities in industrial organizations from raw material procurement to final product delivery to customers. The main aim in supply chain management is to satisfy production requirements, while optimizing the economic objectives. In traditional fossil fuel supply chains, huge amounts of fossil fuels are transported via pipelines or tankers with very small costs. These fuels can be transformed into other sources of energy or transportation fuels at their destination points.
The United States shares with many other countries the goal of the United Nations Framework Convention on Climate Change “to achieve . . . stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system.”1 The critical role of new technologies in achieving this goal is underscored by the fact that most anthropogenic greenhouse gases (GHGs) emitted over the next century will come from equipment and infrastructure that has not yet been built.
There is typically a high degree of flexibility associated with the production of alternative fuels due to the ability to source from different input raw materials or to produce different output products based on market conditions. In this paper, we consider the particular example of ethanol and seek to quantify the incremental value from flexibility in its production from sugarcane in Brazil.
The Biomass and Bioenergy Research Group (BBRG) is a multi-department, multi-disciplinary team at the University of British Columbia in Vancouver, Canada. BBRG conducts innovative research in biomass densification, preprocessing, resource management, material characterization, and supply logisitcs. BBRG bridges the gap between biomass sourcing and biomass conversion, i.e. 'feedstock engineering' - integrating all the processes and management strategies involved from biomass harvest until just prior to final conversion to bioenergy, and bioproducts such as chemicals.
Converting forest lands into bioenergy agriculture could accelerate climate change by emitting carbon stored in forests, while converting food agriculture lands into bioenergy agriculture could threaten food security. Both problems are potentially avoided by using abandoned agriculture lands for bioenergy agriculture. Here we show the global potential for bioenergy on abandoned agriculture lands to be less than 8% of current primary energy demand, based on historical land use data, satellite-derived land cover data, and global ecosystem modeling.
The U.S. Geological Survey (USGS) 2001 National Land Cover Database (NLCD) was compared to the U.S. Department of Agriculture (USDA) 2002 Census of Agriculture. Wecompared areal estimates for cropland at the state and county level for 14 States in the Upper Midwest region of the United States. Absolute differences between the NLCD and Census cropland areal estimates at the state level ranged from 1.3% (Minnesota) to 37.0% (Wisconsin). The majority of counties (74.5%) had differences of less than 100 km2. 7.2% of the counties had differences of more than 200 km2.
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.
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.
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.
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?