The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions

Oda, Tomohiro; Maksyutov, Shamil; Andres, Robert J.

doi:10.5194/essd-10-87-2018

Title: The Open-source Data Inventory for Anthropogenic CO₂, version 2016 (ODIAC2016): a global monthly fossil fuel CO₂ gridded emissions data product for tracer transport simulations and surface flux inversions

Journal Article · Thu Jan 18 00:00:00 EST 2018 · Earth System Science Data (Online)

DOI:https://doi.org/10.5194/essd-10-87-2018· OSTI ID:1474477

Oda, Tomohiro ^[1];

^[2];

^[3]

NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States). Global Modeling and Assimilation Office; Universities Space Research Association (USRA), Columbia, MD (United States). Goddard Earth Sciences Technology and Research
National Inst. for Environmental Studies (NIES), Tsukuba (Japan). Center for Global Environmental Research
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Carbon Dioxide Information Analysis Center

The Open-source Data Inventory for Anthropogenic CO₂ (ODIAC) is a global high-spatial-resolution gridded emissions data product that distributes carbon dioxide (CO₂) emissions from fossil fuel combustion. The emissions spatial distributions are estimated at a 1 × 1 km spatial resolution over land using power plant profiles (emissions intensity and geographical location) and satellite-observed nighttime lights. This work describes the year 2016 version of the ODIAC emissions data product (ODIAC2016) and presents analyses that help guide data users, especially for atmospheric CO₂ tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emissions modeling framework in order to deliver a comprehensive global gridded emissions data product. Major changes from the 2011 publication are (1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring, and international aviation and marine bunkers); (2) the use of multiple spatial emissions proxies by fuel type such as (a) nighttime light data specific to gas flaring and (b) ship/aircraft fleet tracks; and (3) the inclusion of emissions temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emissions data product that covers 2000–2015. Our emissions data can be viewed as an extended version of CDIAC gridded emissions data product, which should allow data users to impose global fossil fuel emissions in a more comprehensive manner than the original CDIAC product. Our new emissions modeling framework allows us to produce future versions of the ODIAC emissions data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. The ODIAC data product could play an important role in supporting carbon cycle science, especially modeling studies with space-based CO₂ data collected in near real time by ongoing carbon observing missions such as the Japanese Greenhouse gases Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory-2 (OCO-2), and upcoming future missions. The ODIAC emissions data product including the latest version of the ODIAC emissions data (ODIAC2017, 2000–2016) is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI (https://doi.org/10.17595/20170411.001).

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Aeronautics and Space Administration (NASA)

Contributing Organization:: National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). National Geophysical Data Center (NGDC)

Grant/Contract Number:: AC05-00OR22725; NNX14AM76G

OSTI ID:: 1474477

Journal Information:: Earth System Science Data (Online), Vol. 10, Issue 1; ISSN 1866-3516

Publisher:: CopernicusCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 213 works

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The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data Eldering, Annmarie; Taylor, Thomas E.; O'Dell, Christopher W. Atmospheric Measurement Techniques, Vol. 12, Issue 4 https://doi.org/10.5194/amt-12-2341-2019	journal	January 2019
Improving the representation of anthropogenic CO₂ emissions in climate models: impact of a new parameterization for the Community Earth System Model (CESM) Navarro, Andrés; Moreno, Raúl; Tapiador, Francisco J. Earth System Dynamics, Vol. 9, Issue 3 https://doi.org/10.5194/esd-9-1045-2018	journal	January 2018
A global map of emission clumps for future monitoring of fossil fuel CO₂ emissions from space Wang, Yilong; Ciais, Philippe; Broquet, Grégoire Earth System Science Data, Vol. 11, Issue 2 https://doi.org/10.5194/essd-11-687-2019	journal	January 2019
EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 Janssens-Maenhout, Greet; Crippa, Monica; Guizzardi, Diego Earth System Science Data, Vol. 11, Issue 3 https://doi.org/10.5194/essd-11-959-2019	journal	January 2019
Simulating atmospheric tracer concentrations for spatially distributed receptors: updates to the Stochastic Time-Inverted Lagrangian Transport model's R interface (STILT-R version 2) Fasoli, Benjamin; Lin, John C.; Bowling, David R. Geoscientific Model Development, Vol. 11, Issue 7 https://doi.org/10.5194/gmd-11-2813-2018	journal	January 2018
A Lagrangian approach towards extracting signals of urban CO₂ emissions from satellite observations of atmospheric column CO₂ (XCO₂): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”) Wu, Dien; Lin, John C.; Fasoli, Benjamin Geoscientific Model Development, Vol. 11, Issue 12 https://doi.org/10.5194/gmd-11-4843-2018	journal	January 2018