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Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design

Super, Ingrid ; Dellaert, Stijn N C ; Visschedijk, Antoon J H ; Hugo A C Denier van der Gon

Atmospheric chemistry and physics, 2020-02, Vol.20 (3), p.1795-1816 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design
Autor: Super, Ingrid ; Dellaert, Stijn N C ; Visschedijk, Antoon J H ; Hugo A C Denier van der Gon
Assuntos: Atmospheric mixing ; Atmospheric models ; Atmospheric transport ; Atmospheric transport models ; Carbon dioxide ; Carbon dioxide emissions ; Carbon monoxide ; Climate change ; Computer simulation ; Disaggregation ; Emission analysis ; Emission inventories ; Emissions ; Greenhouse effect ; Greenhouse gases ; High resolution ; Mitigation ; Mixing ratio ; Modelling ; Network design ; Ratios ; Resolution ; Statistical analysis ; Statistical methods ; Temporal distribution ; Transport processes ; Uncertainty ; Uncertainty analysis
É parte de: Atmospheric chemistry and physics, 2020-02, Vol.20 (3), p.1795-1816
Descrição: Quantification of greenhouse gas emissions is receiving a lot of attention because of its relevance for climate mitigation. Complementary to official reported bottom-up emission inventories, quantification can be done with an inverse modelling framework, combining atmospheric transport models, prior gridded emission inventories and a network of atmospheric observations to optimize the emission inventories. An important aspect of such a method is a correct quantification of the uncertainties in all aspects of the modelling framework. The uncertainties in gridded emission inventories are, however, not systematically analysed. In this work, a statistically coherent method is used to quantify the uncertainties in a high-resolution gridded emission inventory of CO2 and CO for Europe. We perform a range of Monte Carlo simulations to determine the effect of uncertainties in different inventory components, including the spatial and temporal distribution, on the uncertainty in total emissions and the resulting atmospheric mixing ratios. We find that the uncertainties in the total emissions for the selected domain are 1 % forCO2 and 6 % for CO. Introducing spatial disaggregation causes a significant increase in the uncertainty of up to 40 % for CO2 and 70 % for CO for specific grid cells. Using gridded uncertainties, specific regions can be defined that have the largest uncertainty in emissions and are thus an interesting target for inverse modellers. However, the largest sectors are usually the best-constrained ones (low relative uncertainty), so the absolute uncertainty is the best indicator for this. With this knowledge, areas can be identified that are most sensitive to the largest emission uncertainties, which supports network design.
Editor: Katlenburg-Lindau: Copernicus GmbH
Idioma: Inglês

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Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design

Super, Ingrid ; Dellaert, Stijn N C ; Visschedijk, Antoon J H ; Hugo A C Denier van der Gon

Katlenburg-Lindau: Copernicus GmbH

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