GISS Global Methane and Livestock Distribution, 1-Degree
d866000
A global high resolution data base of animal population densities and associated methane (CH4) emissions has been developed at the NASA Goddard Institute for Space Studies (NASA/GISS). The animal population statistics were based primarily on the Food and Agriculture Organization (FAO) compilations and other sources. The animals were distributed using a 1-degree by 1-degree resolution data base of countries and land-use (Matthews, 1983). The animals included are cattle and dairy cows, water buffalo, sheep, goats, camels, pigs, horses, and caribou. Estimates of methane production from each animal type were applied to the animal populations to yield a global distribution of methane emissions by animals. About 55% of the global annual emissions was concentrated between 25 N and 55 N. Estimates of methane emissions from animals were based on the research by Crutzen et al. (1986).
dataset
https://rda.ucar.edu/datasets/d866000/
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https://rda.ucar.edu/datasets/d866000/dataaccess/
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biota
dataset
revision
2014-10-16
GRIDDING METHODS
revision
2024-07-23
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC CHEMISTRY > CARBON AND HYDROCARBON COMPOUNDS > METHANE
revision
2024-07-24
-180
180
90
-90
1972
1982
publication
1989-07-20
notPlanned
Creative Commons Attribution 4.0 International License
None
UCAR/NCAR - Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
(303)-497-1825
303-497-1291
pointOfContact
NCAR Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
303-497-1291
name: NCAR Research Data Archive
description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.
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2024-08-04T02:11:48Z