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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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GMD | Articles | Volume 13, issue 4
Geosci. Model Dev., 13, 2095–2107, 2020
https://doi.org/10.5194/gmd-13-2095-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 13, 2095–2107, 2020
https://doi.org/10.5194/gmd-13-2095-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 28 Apr 2020

Development and technical paper | 28 Apr 2020

Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields

Luke M. Western et al.

Model code and software

INLA_GHG_GMD L. M. Western https://doi.org/10.17605/OSF.IO/53W96

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Short summary
Assessments of greenhouse gas emissions using atmospheric measurements and meteorological models, or top-down methods, are important to verify national inventories or produce a stand-alone estimate where no inventory exists. We present a novel top-down method to estimate emissions. This approach uses a fast method called an integrated nested Laplacian approximation to estimate how these emissions are correlated with other emissions in different locations and at different times.
Assessments of greenhouse gas emissions using atmospheric measurements and meteorological...
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