21 citations as recorded by crossref.

1. HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 1: global and regional module M. Guevara et al. 10.5194/gmd-12-1885-2019
2. Thoughts on Earth System Modeling: From global to regional scale E. Canepa & P. Builtjes 10.1016/j.earscirev.2017.06.017
3. Impact of a future H 2 transportation on atmospheric pollution in Europe M. Popa et al. 10.1016/j.atmosenv.2015.03.022
4. Understanding emissions of ammonia from buildings and application of fertilizers: an example from Poland M. Werner et al. 10.5194/bgd-12-2021-2015
5. Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model F. Kuik et al. 10.5194/acp-18-8203-2018
6. HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 2: The bottom–up module M. Guevara et al. 10.5194/gmd-13-873-2020
7. A multi-meteorological comparison for episodes of PM10 concentrations in the Berlin agglomeration area in Germany with the LOTOS-EUROS CTM M. Thürkow et al. 10.1016/j.atmosenv.2020.117946
8. Spatially valid data of atmospheric deposition of heavy metals and nitrogen derived by moss surveys for pollution risk assessments of ecosystems W. Schröder et al. 10.1007/s11356-016-6577-5
9. Understanding emissions of ammonia from buildings and the application of fertilizers: an example from Poland M. Werner et al. 10.5194/bg-12-3623-2015
10. A top-down assessment using OMI NO<sub>2</sub> suggests an underestimate in the NO<sub><i>x</i></sub> emissions inventory in Seoul, South Korea, during KORUS-AQ D. Goldberg et al. 10.5194/acp-19-1801-2019
11. Optimizing a dynamic fossil fuel CO<sub>2</sub> emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO<sub>2</sub>, CO, NO<sub><i>x</i></sub>, and SO<sub>2</sub> I. Super et al. 10.5194/gmd-13-2695-2020
12. Modeling organic aerosol composition at the puy de Dôme mountain (France) for two contrasted air masses with the WRF-Chem model C. Barbet et al. 10.5194/acpd-15-13395-2015
13. Evaluation of modeling NO<sub>2</sub> concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China F. Liu et al. 10.5194/acp-18-4171-2018
14. Source apportionment of PM2.5 across China using LOTOS-EUROS R. Timmermans et al. 10.1016/j.atmosenv.2017.06.003
15. Modeling emissions for three-dimensional atmospheric chemistry transport models V. Matthias et al. 10.1080/10962247.2018.1424057
16. Implementation of plume rise and its impacts on emissions and air quality modelling M. Guevara et al. 10.1016/j.atmosenv.2014.10.029
17. Performance of European chemistry transport models as function of horizontal resolution M. Schaap et al. 10.1016/j.atmosenv.2015.04.003
18. Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia S. Lopez-Restrepo et al. 10.3390/atmos12010091
19. Enhanced CAMx source apportionment analysis at an urban receptor in Milan based on source categories and emission regions N. Pepe et al. 10.1016/j.aeaoa.2019.100020
20. Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model A. Manders et al. 10.5194/gmd-10-4145-2017
21. Comparison of tropospheric NO<sub>2</sub> columns from MAX-DOAS retrievals and regional air quality model simulations A. Blechschmidt et al. 10.5194/acp-20-2795-2020