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Uncertainty in gridded CO 2 emissions estimates
Author(s) -
Hogue Susannah,
Marland Eric,
Andres Robert J.,
Marland Gregg,
Woodard Dawn
Publication year - 2016
Publication title -
earth's future
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.641
H-Index - 39
ISSN - 2328-4277
DOI - 10.1002/2015ef000343
Subject(s) - magnitude (astronomy) , grid , population , grid cell , environmental science , latitude , proxy (statistics) , longitude , uncertainty analysis , scale (ratio) , meteorology , econometrics , geography , statistics , geodesy , mathematics , physics , cartography , demography , astronomy , sociology
We are interested in the spatial distribution of fossil‐fuel‐related emissions of CO 2 for both geochemical and geopolitical reasons, but it is important to understand the uncertainty that exists in spatially explicit emissions estimates. Working from one of the widely used gridded data sets of CO 2 emissions, we examine the elements of uncertainty, focusing on gridded data for the United States at the scale of 1° latitude by 1° longitude. Uncertainty is introduced in the magnitude of total United States emissions, the magnitude and location of large point sources, the magnitude and distribution of non‐point sources, and from the use of proxy data to characterize emissions. For the United States, we develop estimates of the contribution of each component of uncertainty. At 1° resolution, in most grid cells, the largest contribution to uncertainty comes from how well the distribution of the proxy (in this case population density) represents the distribution of emissions. In other grid cells, the magnitude and location of large point sources make the major contribution to uncertainty. Uncertainty in population density can be important where a large gradient in population density occurs near a grid cell boundary. Uncertainty is strongly scale‐dependent with uncertainty increasing as grid size decreases. Uncertainty for our data set with 1° grid cells for the United States is typically on the order of ±150%, but this is perhaps not excessive in a data set where emissions per grid cell vary over 8 orders of magnitude.

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