Articles | Volume 21, issue 6
Atmos. Chem. Phys., 21, 5117–5136, 2021
https://doi.org/10.5194/acp-21-5117-2021
Atmos. Chem. Phys., 21, 5117–5136, 2021
https://doi.org/10.5194/acp-21-5117-2021
Research article
01 Apr 2021
Research article | 01 Apr 2021

Systematic detection of local CH4 anomalies by combining satellite measurements with high-resolution forecasts

Jérôme Barré et al.

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Cited articles

Barré, J., Massart, S., Ades, M., Jones, L., and Engelen, R.: Emission optimisations first attempt based on Ensemble of Data Asssimilation for atmospheric composition, ECMWF, ECMWF technical memorada, https://doi.org/10.21957/4grkg5ga0, 2019. 
Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Villani, M. G., Houweling, S., Dentener, F., Dlugokencky, E. J., Miller, J. B., Gatti, L. V., Engel, A., and Levin, I.: Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals, J. Geophys. Res., 114, D22301, https://doi.org/10.1029/2009JD012287, 2009. 
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Short summary
This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
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