High resolution gridded emission inventories have significant added value for modelling at the local/city level, allowing larger concentration gradients due to emission being averaged over a smaller area. The local influence of relatively small but diffuse emission sources becomes better visible at higher resolutions and is crucial for the verification of emission inventories using in-situ or satellite observations.
This document reports on progress and current status regarding the “High resolution scenarios of CO2 and CO emissions” developed within CHE WP4. The scope of WP4 “Coordinating Efforts on Attributing CO2 emissions from in-situ measurements” is to explore the practical implications of distinguishing between CO2 fluxes from fossil fuel and biofuel combustion.
This deliverable report describes the compilation of the high resolution scenarios, which are the product of combining a high resolution gridded emission inventory and a consistent assessment of associated uncertainties. The dataset covers the GHGs: CO2 (distinguishing between fossil fuel CO2 and biofuel CO2), methane (CH4) and key co-emitted species that may be used as tracers: CO (also distinguishing between fossil and biofuel), nitrogen oxides (NOx) and non-methane volatile organic compounds (NMVOC).
The features of the high resolution scenarios include:
- High resolution (1/60° x 1/120°; ~1x1km) regional gridded emission inventory for a zoom domain in Europe (-2° W – 19° E, 47° N – 56°N), with point sources (industry and power plants) at their actual location.
- Emission inventory is consistent with TNO gridded emission inventory at 1/10° x 1/20° (~6x6km).
- For CO2 and CO emissions, a distinction is made between emissions from fossil fuel and from biofuel combustion.
- Statistically coherent assessment of associated uncertainties in activity data, emission factors, spatial and temporal distribution.
The high resolution inventory described is used in WP2 for nesting the Berlin high resolution spatially distributed emissions from the Berlin Senate (see CHE D2.3; Denier van der Gon et al, 2019) to facilitate the WP2 modelling case study over Berlin.