Water consumption and water quality continue to be key factors affecting environmental sustainability in biofuel production. This review covers the findings from biofuel water analyses published over the past 2 years to underscore the progress made, and to highlight advancements in understanding the interactions among increased production and water demand, water resource availability, and potential changes in water quality. We focus on two key areas: water footprint assessment and watershed modeling. Results revealed that miscanthus-, switchgrass-, and forest wood-based biofuels all have promising blue and grey water footprints. Alternative water resources have been explored for algae production, and challenges remain. A most noticeable improvement in the analysis of life-cycle water consumption is the adoption of geospatial analysis and watershed modeling to generate a spatially explicit water footprint at a finer scale (e.g., multi-state region, state, and county scales) to address the impacts of land use change and climate on the water footprint in a landscape with a mixed biofuel feedstock.
NREL's energy-water modeling and analysis activities analyze the interactions and dependencies of water with the dynamics of the power sector and the transportation sector. A variety of models and tools are utilized to consider water as a critical resource for power sector development and operations as well as transportation fuels.
Specifically, the biomass feedstock water analysis focuses on characterizing the geospatial and temporal dynamics of biomass feedstock water requirements. Water requirements for biomass feedstocks can vary geographically and can require different types of water inputs (e.g., rainfall vs. irrigation), which can affect the suitability and sustainability of biomass pathways.
A broad-scale perspective on the nexus between climate change, land use, and energy requires consideration of interactions that were often omitted from climate change studies. While prior analyses have considered how climate change affects land use and vice versa (Dale 1997), there is growing awareness of the need to include energy within the analytical framework. A broad-scale perspective entails examining patterns and process at divers spatial and temporal resolutions.
Governments worldwide are promoting the development of biofuels in order to mitigate the climate impact of using fuels. In this article, I discuss the impacts of biofuels on climate change, water use, and land use. I discuss the overall metric by which these impacts have been measured and then present and discuss estimates of the impacts. In spite of the complexities of the environmental and technological systems that affect climate change, land use, and water use, and the difficulties of constructing useful metrics, it is possible to make some qualitative overall assessments. It is likely that biofuels produced from crops using conventional agricultural practices will not mitigate the impacts of climate change and will exacerbate stresses on water supplies, water quality, and land use, compared with petroleum fuels. Policies should promote the development of sustainable biofuel programs that have very low inputs of fossil fuels and chemicals that rely on rainfall or abundant groundwater, and that use land with little or no economic or ecological value in alternative uses.
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. As a result, new technologies and fuels have the potential to transform the nation’s energy system while meeting climate change as well as energy security and other goals.
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
map is still missing. Based on recent data sets from the Climatic Research Unit (CRU) of the University of
East Anglia and the Global Precipitation Climatology Centre (GPCC) at the German Weather Service, we
present here a new digital Köppen-Geiger world map on climate classification, valid for the second half of
the 20th century.
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. Here, we present a series of digital world maps for the extended period 1901-2100 to depict global trends in observed climate and projected climate change scenarios.World maps for the observational period 1901-2002 are based on recent data sets from the Climatic Research Unit (CRU) of the University of East Anglia and the Global Precipitation Climatology Centre (GPCC) at the German Weather Service. World maps for the period 2003–2100 are based on ensemble projections of global climate models provided by the Tyndall Centre for Climate Change Research. The main results comprise an estimation of the shifts of climate zones within the 21st century by considering different IPCC scenarios. The largest shifts between the main classes of equatorial climate (A), arid climate (B), warm temperate climate (C), snow climate (D) and polar climate (E) on global land areas are estimated as 2.6–3.4 % (E to D), 2.2–4.7 % (D to C), 1.3–2.0 (C to B) and 2.1–3.2 % (C to A).
The underlying data of the Köppen-Geiger climate classification maps are available for free for use in scientific research and can be obtained as zipped ASCII-files, shape files for GIS software, or as KMZ files for use in Google Earth.
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. Additionally, environmental and economic conditions, including soil quality, climate, and variable agricultural costs, vary significantly across Illinois. The intent of this study is to examine the spatial and economic conditions necessary for introducing bioenergy crops into the Illinois landscape. In this paper, we develop a spatial dynamic model to explore the process by which individual farmer agents optimize profits through crop selection and cost minimization. This dynamic agent-based modeling approach will allow us to determine the optimal spatial arrangement of crops throughout Illinois as it is influenced by several factors, including the use of subsidies, changes in travel costs and crop demand, and the introduction of new ethanol production plants. This article discusses model development and specification, and outlines future calibration procedures and scenario tests that will be formalized in future work.
This paper presents a range of future, spatially explicit, land use change scenarios for the EU15, Norway and Switzerland based on an interpretation of the global storylines of the Intergovernmental Panel on Climate Change (IPCC) that are presented in the special report on emissions scenarios (SRES). The methodology is based on a qualitative interpretation of the SRES storylines for the European region, an estimation of the aggregate totals of land use change using various land use change models and the allocation of these aggregate quantities in space using spatially explicit rules. The spatial patterns are further downscaled from a resolution of 10 min to 250 m using statistical downscaling procedures. The scenarios include the major land use/land cover classes urban, cropland, grassland and forest land as well as introducing new land use classes such as bioenergy crops. The scenario changes are most striking for the agricultural land uses, with large area declines resulting from assumptions about future crop yield development with respect to changes in the demand for agricultural commodities. Abandoned agricultural land is a consequence of these assumptions. Increases in urban areas (arising from population and economic change) are similar for each scenario, but the spatial patterns are very different. This reflects alternative assumptions about urban development processes. Forest land areas increase in all scenarios, although such changes will occur slowly and largely reflect assumed policy objectives. The scenarios also consider changes in protected areas (for conservation or recreation goals) and how these might provide a break on future land use change. The approach to estimate new protected areas is based in part on the use of models of species distribution and richness. All scenarios assume some increases in the area of bioenergy crops with some scenarios assuming a major development of this new land use. Several technical and conceptual difficulties in developing future land use change scenarios are discussed. These include the problems of the subjective nature of qualitative interpretations, the land use change models used in scenario development, the problem of validating future change scenarios, the quality of the observed baseline, and statistical downscaling techniques.
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. Land-use change is driven by synergetic factor combinations of resource scarcity leading to an increase in the pressure of production on resources, changing opportunities created by markets, outside policy intervention, loss of adaptive capacity, and changes in social organization and attitudes. The changes in ecosystem goods and services that result from land-use change feed back on the drivers of land-use change. A restricted set of dominant pathways of land-use change is identified. Land-use change can be understood using the concepts of complex adaptive systems and transitions. Integrated, place-based research on land-use/land-cover change requires a combination of the agent-based systems and narrative perspectives of understanding. We argue in this paper that a systematic analysis of local-scale land-use change studies, conducted over a range of timescales, helps to uncover general principles that provide an explanation and prediction of new land-use changes.