global

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.

http://jgcri.github.io/gcam-doc/

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. We critically review modeling approaches employed to estimate biofuel-induced LUC and identify major challenges, important research gaps, and limitations of LUC studies for transportation fuels. We found LUC modeling philosophies and model structures and features (e.g. dynamic vs. static model) significantly differ among studies. Variations in estimated GHG emissions from biofuel-induced LUC are also driven by differences in scenarios assessed, varying assumptions, inconsistent definitions (e.g. LUC), subjective selection of reference scenarios against which (marginal) LUC is quantified, and disparities in data availability and quality. The lack of thorough sensitivity and uncertainty analysis hinders the evaluation of plausible ranges of estimates of GHG emissions from LUC. The relatively limited fuel coverage in the literature precludes a complete set of direct comparisons across alternative and conventional fuels sought by regulatory bodies and researchers.

Improved modeling approaches, consistent definitions and classifications, availability of high-resolution data on LUC over time, development of standardized reference and future scenarios, incorporation of non-economic drivers of LUC, and more rigorous treatment of uncertainty can help improve LUC estimates in effectively achieving policy goals.

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. The OBP International Sustainability activities contributed to the Bioenergy chapter, technology cost annex as well as lifecycle assessments and sustainability information.

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. biofuel policy have centered on the global social and environmental implications of land use. In particular, there is an ongoing debate about whether “indirect land use change” (ILUC) would cause biofuels to become a net source, rather than sink, of carbon emissions. Estimates of ILUC induced by biofuel production can only be inferred through modeling. This paper evaluates how model structure, underlying assumptions, and the representation of policy instruments influence the results of U.S. biofuel policy simulations. The analysis shows that differences in these factors can lead to divergent model estimates of land use and economic effects. Model estimates of the net conversion of forests and grasslands induced by U.S. biofuel policy range from 0.09 ha/1000 gallons described in this paper to 0.73 ha/1000 gallons from early studies in the ILUC change debate. We note that several important factors governing LUC change remain to be examined. Challenges that must be addressed to improve global land use change modeling are highlighted.

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. These products vary in GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values to grid cells. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. The Spatial Reference metadata section information applies only to global extent, 30 arc-second resolution. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).

An updated Gridded Population of the World, Version 4 (GPWv4) is now available.

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. These products vary in GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).

Gridded Population of the World, Version 4 (GPWv4) is now available.

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.
 
 
 
 

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.