Authors: Tomohiro Oda*, Universities Space Research Association/NASA Goddard, Thomas Lauvaux , Laboratoire des sciences du climat et de l'environnement, Gif sur Yvette, France, Shamil Maksyutov, Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan, Miguel Roman, Earth from Space Institute, Universities Space Research Association, Columbia, MD, USA, Zhuosen Wang, Terrestrial Information Systems Laboratory, NASA Goddard Space Flight Center, MD, USA, Sha Feng, Department of Meteorology and Atmospheric Science, Penn State, State Collage, PA, USA , Rostyslav Bun, Lviv Polytechnic National University, Lviv, Ukraine/WSB University, Dąbrowa Górnicza, Poland, Vitaliy Kinakh , Lviv Polytechnic National University, Lviv, Ukraine, Lesley Ott, Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA, Steven Pawson, Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Topics: Remote Sensing, Environmental Science, Human-Environment Geography
Keywords: Greenhouse gas, remote sensing, environmental change, global warming, CO2, urban, cities, global
Session Type: Poster
Start / End Time: 8:00 AM / 9:40 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded
Carbon dioxide (CO2) emissions from fossil fuel combustion are the main cause of the observed, increasing atmospheric CO2 concentration. The emissions need to be closely monitored and then curved in order to keep the global temperature rise well below 2 degree Celsius above pre-industrial levels. The emissions are often quantified with reasonable accuracy via compilation of emission inventories at the country level. However, a new challenge under the Paris Climate Agreement is accurately monitoring emission changes at the subnational levels, such as cities and large point sources.
We have been explored the use of space-based observations (e.g. nighttime lights) to map human-induced CO2 emissions. Our global high-resolution CO2 emission model ODIAC distributes country level emission estimates using point source information and satellite-observations of nightlights. The use of nightlight data allows us to detect dynamic changes in emissions spatial distributions in a timely manner and incorporate those into the high-resolution emission field. To further improve the accuracy of the spatial emission estimates, we have been examining NASA’s “Black Marble” Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Environmental Product.
The science community has been working towards the establishment of future Monitoring and Verification Support (MVS) systems. Although emission inventories are prone to systematic biases, future MVS systems should allow us to confirm the reported emissions using independent atmospheric observations in order to monitor the compliance of emission reduction across different spatial scales. Our advanced satellite-based emission model holds a promise of playing a critical role in future MVS frameworks.