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Energies 2010, 3(12), 1895-1913; doi:10.3390/en3121895

Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery

1,* , 2
1 Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA 2 Earth Observation Group, Solar and Terrestrial Physics Division, NOAA National Geophysical Data Center, 325 Broadway, Boulder, CO 80305, USA 3 Department of Geography, University of Denver, Denver, CO 80208, USA
* Author to whom correspondence should be addressed.
Received: 21 November 2010 / Revised: 6 December 2010 / Accepted: 7 December 2010 / Published: 8 December 2010
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The potential use of satellite observed nighttime lights for estimating carbon-dioxide (CO2) emissions has been demonstrated in several previous studies. However, the procedures for a moderate resolution (1 km2 grid cells) global map of fossil fuel CO2 emissions based on nighttime lights are still in the developmental phase. We report on the development of a method for mapping distributed fossil fuel CO2 emissions (excluding electric power utilities) at 30 arc-seconds or approximately 1 km2 resolution using nighttime lights data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). A regression model, Model 1, was initially developed based on carbon emissions from five sectors of the Vulcan data produced by the Purdue University and a nighttime satellite image of the U.S. The coefficient derived through Model 1 was applied to the global nighttime image but it resulted in underestimation of CO2 emissions for most of the world’s countries, and the states of the U.S. Thus, a second model, Model 2 was developed by allocating the distributed CO2 emissions (excluding emissions from utilities) using a combination of DMSP-OLS nighttime image and population count data from the U.S. Department of Energy's (DOE) LandScan grid. The CO2 emissions were distributed in proportion to the brightness of the DMSP nighttime lights in areas where lighting was detected. In areas with no DMSP detected lighting, the CO2 emissions were distributed based on population count, with the assumption that people who live in these areas emit half as much CO2 as people who live in the areas with DMSP detected lighting. The results indicate that the relationship between satellite observed nighttime lights and CO2 emissions is complex, with differences between sectors and variations in lighting practices between countries. As a result it is not possible to make independent estimates of CO2 emissions with currently available coarse resolution panchromatic satellite observed nighttime lights. However, the nighttime lights image in conjunction with the population grid can help in more accurate disaggregation of national CO2 emissions to a moderate resolution spatial grid.
Keywords: CO2 grid; nighttime satellite image; LandScan population grid CO2 grid; nighttime satellite image; LandScan population grid
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Ghosh, T.; Elvidge, C.D.; Sutton, P.C.; Baugh, K.E.; Ziskin, D.; Tuttle, B.T. Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery. Energies 2010, 3, 1895-1913.

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