Applying satellite observations to improve bottom-up national emission inventories for methane: application to Colombia
12 affiliations
- 1Harvard University (Cambridge, United States of America)
- 2Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, 02138, USA
- 3Department of Chemical and Environmental Engineering, Universidad Nacional de Colombia–Bogotá, Bogotá, Colombia
- 4Earth Sciences Department, Royal Holloway University of London, Egham, Surrey, UK
- 5Environmental Defense Fund Europe, Avenue des Arts 47–49, Brussels, Belgium
- 6Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- 7Massachusetts Institute of Technology, Institute for Data, Systems, and Society, Cambridge, MA, 02139, USA
- 8California Institute of Technology, Division of Geological and Planetary Sciences, Pasadena, CA, USA
- 9Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- 10International Methane Emissions Observatory (IMEO), United Nations Environment Programme (UNEP), Paris, France
- 11Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
- 12National Centre for Earth Observation, University of Leicester, Leicester, UK
Abstract
Countries report bottom-up inventories of methane emissions under the Paris Agreement to the United Nations Framework Convention on Climate Change (UNFCCC), but these inventories can have large uncertainties in activity data and emission factors. Top-down information from inversion of satellite observations can provide valuable constraints to improve these estimates, but has been limited by coarse resolution and the use of inadequate emission inventories as prior estimates. Here, we combine inventory and atmospheric data to quantify 2023 national emissions in Colombia. We use satellite observations from TROPOMI, GOSAT, and point source imagers (GHGSat, EMIT, aircraft AVIRIS-NG) in an analytical inversion at ≈12×12 km2 resolution with the Integrated Methane Inversion v2.0 framework. We construct a spatially-resolved version of the national bottom-up emission inventory from the Biennial Update Report (BUR) to the UNFCCC for use as prior estimate in the inversion, and combine it with high-resolution wetland extent data (GLWDv2) to separate anthropogenic from wetland emissions. Total posterior methane emissions are 8.9 (8.7–9.1) Tg a-1 contributed by wetlands (5.7 (5.5–6.0) Tg a-1) and anthropogenic emissions (3.2 (3.1–3.2) Tg a-1), mainly livestock (2.0 (1.9–2.1) Tg a-1) and waste (0.76 (0.74–0.76) Tg a-1). Adjustments relative to the BUR are +18 % for livestock, +19 % for waste, +60 % for oil/gas, and +92 % for coal. We provide recommendations to improve the BUR, offering a blueprint for combining satellite observations with national inventory data to produce sectorally and spatially resolved emissions estimates that can inform mitigation planning.
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BibTeX
@article{hancock2026applying,
title = {{Applying satellite observations to improve bottom-up national emission inventories for methane: application to Colombia}},
author = {Sarah E. Hancock and Daniel J. Jacob and Rodrigo Jiménez and Andres V. Ardila and Luis A. Morales-Rincon and Néstor Y. Rojas and Lucas Estrada and Nicholas Balasus and James D. East and Melissa Payer Sulprizio and Xiaolin Wang and James Lawrence France and Lauren Potyk and Elise Penn and Zichong Chen and Daniel J. Varon and Christian Frankenberg and Marci Rose Baranski and Andreea Calcan and Robert J. Parker},
journal = {Atmospheric chemistry and physics},
year = {2026},
month = jul,
doi = {10.5194/acp-26-10455-2026},
url = {https://doi.org/10.5194/acp-26-10455-2026},
note = {CC BY},
}
RIS
TY - JOUR
TI - Applying satellite observations to improve bottom-up national emission inventories for methane: application to Colombia
AU - Sarah E. Hancock
AU - Daniel J. Jacob
AU - Rodrigo Jiménez
AU - Andres V. Ardila
AU - Luis A. Morales-Rincon
AU - Néstor Y. Rojas
AU - Lucas Estrada
AU - Nicholas Balasus
AU - James D. East
AU - Melissa Payer Sulprizio
AU - Xiaolin Wang
AU - James Lawrence France
AU - Lauren Potyk
AU - Elise Penn
AU - Zichong Chen
AU - Daniel J. Varon
AU - Christian Frankenberg
AU - Marci Rose Baranski
AU - Andreea Calcan
AU - Robert J. Parker
PY - 2026
DA - 2026/07/27
JO - Atmospheric chemistry and physics
DO - 10.5194/acp-26-10455-2026
UR - https://doi.org/10.5194/acp-26-10455-2026
AB - Countries report bottom-up inventories of methane emissions under the Paris Agreement to the United Nations Framework Convention on Climate Change (UNFCCC), but these inventories can have large uncertainties in activity data and emission factors. Top-down information from inversion of satellite observations can provide valuable constraints to improve these estimates, but has been limited by coarse resolution and the use of inadequate emission inventories as prior estimates. Here, we combine inventory and atmospheric data to quantify 2023 national emissions in Colombia. We use satellite observations from TROPOMI, GOSAT, and point source imagers (GHGSat, EMIT, aircraft AVIRIS-NG) in an analytical inversion at ≈12×12 km2 resolution with the Integrated Methane Inversion v2.0 framework. We construct a spatially-resolved version of the national bottom-up emission inventory from the Biennial Update Report (BUR) to the UNFCCC for use as prior estimate in the inversion, and combine it with high-resolution wetland extent data (GLWDv2) to separate anthropogenic from wetland emissions. Total posterior methane emissions are 8.9 (8.7–9.1) Tg a-1 contributed by wetlands (5.7 (5.5–6.0) Tg a-1) and anthropogenic emissions (3.2 (3.1–3.2) Tg a-1), mainly livestock (2.0 (1.9–2.1) Tg a-1) and waste (0.76 (0.74–0.76) Tg a-1). Adjustments relative to the BUR are +18 % for livestock, +19 % for waste, +60 % for oil/gas, and +92 % for coal. We provide recommendations to improve the BUR, offering a blueprint for combining satellite observations with national inventory data to produce sectorally and spatially resolved emissions estimates that can inform mitigation planning.
SN - 1680-7316
SN - 1680-7324
ER -