Articles | Volume 13, issue 5
https://doi.org/10.5194/gmd-13-2379-2020
https://doi.org/10.5194/gmd-13-2379-2020
Development and technical paper
 | 
26 May 2020
Development and technical paper |  | 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, Gerrit Kuhlmann, Qing Mu, Jean-Matthieu Haussaire, David Ochsner, Katherine Osterried, Valentin Clément, and Dominik Brunner

Related authors

Wildfires as a source of airborne mineral dust – revisiting a conceptual model using large-eddy simulation (LES)
Robert Wagner, Michael Jähn, and Kerstin Schepanski
Atmos. Chem. Phys., 18, 11863–11884, https://doi.org/10.5194/acp-18-11863-2018,https://doi.org/10.5194/acp-18-11863-2018, 2018
Short summary
Airborne observations of newly formed boundary layer aerosol particles under cloudy conditions
Barbara Altstädter, Andreas Platis, Michael Jähn, Holger Baars, Janine Lückerath, Andreas Held, Astrid Lampert, Jens Bange, Markus Hermann, and Birgit Wehner
Atmos. Chem. Phys., 18, 8249–8264, https://doi.org/10.5194/acp-18-8249-2018,https://doi.org/10.5194/acp-18-8249-2018, 2018
Short summary

Related subject area

Atmospheric sciences
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024,https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024,https://doi.org/10.5194/gmd-17-5041-2024, 2024
Short summary
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024,https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024,https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024,https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary

Cited articles

Athanasopoulou, E., Vogel, H., Vogel, B., Tsimpidi, A. P., Pandis, S. N., Knote, C., and Fountoukis, C.: Modeling the meteorological and chemical effects of secondary organic aerosols during an EUCAARI campaign, Atmos. Chem. Phys., 13, 625–645, https://doi.org/10.5194/acp-13-625-2013, 2013. a
Athanasopoulou, E., Speyer, O., Brunner, D., Vogel, H., Vogel, B., Mihalopoulos, N., and Gerasopoulos, E.: Changes in domestic heating fuel use in Greece: effects on atmospheric chemistry and radiation, Atmos. Chem. Phys., 17, 10597–10618, https://doi.org/10.5194/acp-17-10597-2017, 2017. a
Baklanov, A., Schlünzen, K., Suppan, P., Baldasano, J., Brunner, D., Aksoyoglu, S., Carmichael, G., Douros, J., Flemming, J., Forkel, R., Galmarini, S., Gauss, M., Grell, G., Hirtl, M., Joffre, S., Jorba, O., Kaas, E., Kaasik, M., Kallos, G., Kong, X., Korsholm, U., Kurganskiy, A., Kushta, J., Lohmann, U., Mahura, A., Manders-Groot, A., Maurizi, A., Moussiopoulos, N., Rao, S. T., Savage, N., Seigneur, C., Sokhi, R. S., Solazzo, E., Solomos, S., Sørensen, B., Tsegas, G., Vignati, E., Vogel, B., and Zhang, Y.: Online coupled regional meteorology chemistry models in Europe: current status and prospects, Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, 2014. a
Baldauf, M., Seifert, A., Forstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/Mwr-D-10-05013.1, 2011. a
Bieser, J., Aulinger, A., Matthias, V., Quante, M., and Builtjes, P.: SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe, Geosci. Model Dev., 4, 47–68, https://doi.org/10.5194/gmd-4-47-2011, 2011a. a
Download
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.