Articles | Volume 20, issue 3
https://doi.org/10.5194/acp-20-1795-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-1795-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Feb 2020
Research article |
| 14 Feb 2020
| 14 Feb 2020
Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Stijn N. C. Dellaert
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Antoon J. H. Visschedijk
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Hugo A. C. Denier van der Gon
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
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Latest update: 20 Nov 2024
Short summary
Emission data contain uncertainties introduced by the methodology and the data used. We quantified uncertainties in gridded emissions using the uncertainty in underlying data, showing that disaggregation in space and time significantly increases the uncertainty. Understanding uncertainties helps to interpret atmospheric measurements and the gap with modelled concentrations. Moreover, our analyses help identify regions with large uncertainties, which require further scrutiny.
Emission data contain uncertainties introduced by the methodology and the data used. We...
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