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A Fine-Scale Global Fossil Fuel and Biomass Burning Emissions Dataset Using Suomi-NPP/VIIRS Satellite Data

Oda, Tomohiro (Tom): USRA (Project Lead)

Project Funding: 2014 - 2017

NRA: 2013 NASA: Carbon Cycle Science   

Funded by NASA

We propose to develop fine-scale global emissions datasets for fossil fuel combustion (for CO2) and biomass burning (for CO2, CO and CH4). Carbon emissions datasets (e.g. for fossil fuel combustion, biospheric exchange and biomass burning) are primary inputs to any study of the global carbon budget, emissions drivers, and associated carbon cycle processes. To capture realistic emissions dynamics, such high-resolution emissions datasets need to be created/updated in a timely manner to accurately reflect emission changes. The use of satellite data for disaggregation of national emissions can allow such time-varying emissions datasets to be generated quickly. Human settlement patterns, inferred from gridded nightlights data collected by Defense Meteorological Satellite Project (DMSP) satellites, have been used as a proxy for human-induced emissions. Nightlights imagery and other data collected by the Visible/Infrared Imager Radiometer Suite (VIIRS) sensors on the Suomi National Polar-orbiting Partnership (NPP) satellite (2011-on) can now be used to significantly improve upon these DMSP-based products. It has been possible to generate the DMSP nightlight data only at a low time frequency, and it is affected by pixel saturation. However, nighttime data collected by the Day/Night band of VIIRS now provides unsaturated nightlight data at higher frequently and spatial resolution than previous instruments on DMSP. The use of VIIRS nightlight data should allow us to significantly improve the current CO2 emission mapping method, giving an accurate and timely view of regions where the intensity and spatial extent of human activities are rapidly changing. We will implement this improvement using the existing Odiac emissions model that has been used to generate a global 1 km x 1 km fossil fuel emission map. In addition, the Nightfire algorithm that identifies combustion sources from VIIRS measurements gives us a unique opportunity to directly estimate emissions from single combustion events that are often missed by the current emissions reporting system. The performance of Nightfire will be tested using air-sampling measurements where available. Leveraging the Nightfire algorithm, which estimates the burnt area of each combustion sources identified, we will also develop a 1km x 1km emissions dataset for biomass burning (for CO2, CO and CH4). Most of the existing biomass burning datasets rely on MODIS data: our proposed work will give an alternative view, since the Nightfire method is different from the algorithm used for the MODIS fire products. We will assimilate Nightfire-derived burnt area data into the Fire INventory from NCAR (FINN) fire model to obtain a new biomass burning emissions estimate. Also, we will use the Data Assimilation Linked Ecosystem Carbon (DALEC) biosphere model to produce a second set of biomass burning emissions, as well as net ecosystem production consistent with biomass burning. Finally, the performance of our new emissions datasets will be assessed by using them as priors in a state-of-the-art flux inversion system, then determining whether the posterior fit to independent measurements (not used in the assimilation) improves compared to the fit from earlier emissions datasets. This proposal is responsive to Theme 4 of the Carbon Dynamics call, 'Urban-Suburban-Forested-Agricultural Landscapes', insofar as it attempts to 'put observational constraints on the atmospheric signature of emission estimates'. Also, this proposed work respondsto the objective stated in Theme 4 by delivering a tool to map dynamically changing emissions. Emissions data derived from VIIRS should also be useful for NASA's upcoming carbon observing missions. Detailed emission maps, for example, allow one to make more realistic observation design tests with Observing System Simulation Experiments (OSSEs).


Gaughan, A. E., Oda, T., Sorichetta, A., Stevens, F. R., Bondarenko, M., Bun, R., Krauser, L., Yetman, G., Nghiem, S. V. 2019. Evaluating nighttime lights and population distribution as proxies for mapping anthropogenic CO2 emission in Vietnam, Cambodia and Laos. Environmental Research Communications. 1(9), 091006. DOI: 10.1088/2515-7620/ab3d91

Hedelius, J. K., Liu, J., Oda, T., Maksyutov, S., Roehl, C. M., Iraci, L. T., Podolske, J. R., Hillyard, P. W., Liang, J., Gurney, K. R., Wunch, D., Wennberg, P. O. 2018. Southern California megacity CO<sub>2</sub>, CH<sub>4</sub>, and CO flux estimates using ground- and space-based remote sensing and a Lagrangian model. Atmospheric Chemistry and Physics. 18(22), 16271-16291. DOI: 10.5194/acp-18-16271-2018

Liu, J., Baskaran, L., Bowman, K., Schimel, D., Bloom, A. A., Parazoo, N. C., Oda, T., Carroll, D., Menemenlis, D., Joiner, J., Commane, R., Daube, B., Gatti, L. V., McKain, K., Miller, J., Stephens, B. B., Sweeney, C., Wofsy, S. 2021. Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020). Earth System Science Data. 13(2), 299-330. DOI: 10.5194/essd-13-299-2021

Oda, T., Bun, R., Kinakh, V., Topylko, P., Halushchak, M., Marland, G., Lauvaux, T., Jonas, M., Maksyutov, S., Nahorski, Z., Lesiv, M., Danylo, O., Horabik-Pyzel, J. 2019. Errors and uncertainties in a gridded carbon dioxide emissions inventory. Mitigation and Adaptation Strategies for Global Change. 24(6), 1007-1050. DOI: 10.1007/s11027-019-09877-2

Oda, T., Maksyutov, S., Andres, R. J. 2018. The Open-source Data Inventory for Anthropogenic CO<sub>2</sub>, version 2016 (ODIAC2016): a global monthly fossil fuel CO<sub>2</sub> gridded emissions data product for tracer transport simulations and surface flux inversions. Earth System Science Data. 10(1), 87-107. DOI: 10.5194/essd-10-87-2018

Wu, D., Lin, J. C., Duarte, H. F., Yadav, V., Parazoo, N. C., Oda, T., Kort, E. A. A Model for Urban Biogenic CO<sub>2</sub> Fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) DOI: 10.5194/gmd-2020-301

Wu, D., Lin, J. C., Duarte, H. F., Yadav, V., Parazoo, N. C., Oda, T., Kort, E. A. A Model for Urban Biogenic CO<sub>2</sub> Fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) DOI: 10.5194/gmd-2020-301

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

  • Recent developments in ODIAC fossil fuel CO2 emission dataset   --   (Tomohiro Oda, Shamil Maksyutov, Robert J Andres, Chris D Elvidge)   [abstract]

More details may be found in the following project profile(s):