Articles | Volume 13, issue 5
https://doi.org/10.5194/gmd-13-2379-2020
© 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/gmd-13-2379-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
26 May 2020
Development and technical paper |
| 26 May 2020
| 26 May 2020
An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1
Michael Jähn
Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
Gerrit Kuhlmann
Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
Qing Mu
Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
now at: Division for Climate Modelling and Air Pollution, Norwegian Meteorological Institute, Oslo, Norway
Jean-Matthieu Haussaire
Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
David Ochsner
Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
Katherine Osterried
Center for Climate Systems Modelling (C2SM), ETH Zurich, Zurich, Switzerland
Valentin Clément
Federal Office for Meteorology and Climatology (MeteoSwiss), Kloten, Switzerland
now at: Oak Ridge National Laboratory, Oak Ridge, TN, USA
Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
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Cited
13 citations as recorded by crossref.
- The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2 B. Murphy et al. 10.5194/gmd-14-3407-2021
- The impact of temporal variability in prior emissions on the optimization of urban anthropogenic emissions of CO2, CH4 and CO using in-situ observations I. Super et al. 10.1016/j.aeaoa.2021.100119
- Evaluation of simulated CO2 power plant plumes from six high-resolution atmospheric transport models D. Brunner et al. 10.5194/acp-23-2699-2023
- Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions I. Katharopoulos et al. 10.5194/acp-23-14159-2023
- Mountain-wave-induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART M. Weimer et al. 10.5194/acp-21-9515-2021
- Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observations P. Shrestha et al. 10.5194/acp-22-14095-2022
- Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites G. Kuhlmann et al. 10.3389/frsen.2021.689838
- European CH4 inversions with ICON-ART coupled to the CarbonTracker Data Assimilation Shell M. Steiner et al. 10.5194/acp-24-2759-2024
- FUME 2.0 – Flexible Universal processor for Modeling Emissions M. Belda et al. 10.5194/gmd-17-3867-2024
- Lagrangian Particle Dispersion Models in the Grey Zone of Turbulence: Adaptations to FLEXPART-COSMO for Simulations at 1 km Grid Resolution I. Katharopoulos et al. 10.1007/s10546-022-00728-3
- Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models H. Lin et al. 10.5194/gmd-14-5487-2021
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- High-resolution inverse modelling of European CH4 emissions using the novel FLEXPART-COSMO TM5 4DVAR inverse modelling system P. Bergamaschi et al. 10.5194/acp-22-13243-2022
13 citations as recorded by crossref.
- The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2 B. Murphy et al. 10.5194/gmd-14-3407-2021
- The impact of temporal variability in prior emissions on the optimization of urban anthropogenic emissions of CO2, CH4 and CO using in-situ observations I. Super et al. 10.1016/j.aeaoa.2021.100119
- Evaluation of simulated CO2 power plant plumes from six high-resolution atmospheric transport models D. Brunner et al. 10.5194/acp-23-2699-2023
- Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions I. Katharopoulos et al. 10.5194/acp-23-14159-2023
- Mountain-wave-induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART M. Weimer et al. 10.5194/acp-21-9515-2021
- Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observations P. Shrestha et al. 10.5194/acp-22-14095-2022
- Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites G. Kuhlmann et al. 10.3389/frsen.2021.689838
- European CH4 inversions with ICON-ART coupled to the CarbonTracker Data Assimilation Shell M. Steiner et al. 10.5194/acp-24-2759-2024
- FUME 2.0 – Flexible Universal processor for Modeling Emissions M. Belda et al. 10.5194/gmd-17-3867-2024
- Lagrangian Particle Dispersion Models in the Grey Zone of Turbulence: Adaptations to FLEXPART-COSMO for Simulations at 1 km Grid Resolution I. Katharopoulos et al. 10.1007/s10546-022-00728-3
- Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models H. Lin et al. 10.5194/gmd-14-5487-2021
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- High-resolution inverse modelling of European CH4 emissions using the novel FLEXPART-COSMO TM5 4DVAR inverse modelling system P. Bergamaschi et al. 10.5194/acp-22-13243-2022
Latest update: 26 Jul 2024
Short summary
Emission inventories of air pollutants and greenhouse gases are widely used as input for atmospheric chemistry transport models. However, the pre-processing of these data is both time-consuming and requires a large amount of disk storage. To overcome this issue, a Python package has been developed and tested for two different models. There, the inventory is projected to the model grid and scaling factors are provided. This approach saves computational time while remaining numerically equivalent.
Emission inventories of air pollutants and greenhouse gases are widely used as input for...
