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

Abstract: 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.