Articles | Volume 14, issue 2
https://doi.org/10.5194/acp-14-939-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-14-939-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Jan 2014
Research article |
| 27 Jan 2014
Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions
A. Mues
Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
now at: IASS Potsdam, Institute for Advanced Sustainability Studies e.V., Berliner Strasse 130, 14467 Potsdam, Germany
J. Kuenen
TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
C. Hendriks
TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
A. Manders
TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
A. Segers
TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
Y. Scholz
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Technische Thermodynamik Systemanalyse und Technikbewertung Pfaffenwaldring 38–40, 70569 Stuttgart, Germany
C. Hueglin
EMPA, Swiss Federal Laboratories for Materials Science and Technology, Überlandstraße 129, 8600 Dübendorf, Switzerland
P. Builtjes
Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
M. Schaap
TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, 3508 TA Utrecht, the Netherlands
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33 citations as recorded by crossref.
- 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
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- Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling A. van der Woude et al. 10.5194/essd-15-579-2023
- Impact of a future H 2 transportation on atmospheric pollution in Europe M. Popa et al. 10.1016/j.atmosenv.2015.03.022
- A Gradient-Descent Optimization of CO2–CO–NOx Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown C. Abdallah et al. 10.1021/acs.est.3c00566
- Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling M. Guevara et al. 10.5194/essd-13-367-2021
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Daily Emission Patterns of Coal-Fired Power Plants in China Based on Multisource Data Fusion N. Wu et al. 10.1021/acsenvironau.2c00014
- Advances in air quality research – current and emerging challenges R. Sokhi et al. 10.5194/acp-22-4615-2022
- Source apportionment of PM2.5 across China using LOTOS-EUROS R. Timmermans et al. 10.1016/j.atmosenv.2017.06.003
- Modeling emissions for three-dimensional atmospheric chemistry transport models V. Matthias et al. 10.1080/10962247.2018.1424057
- Implementation of plume rise and its impacts on emissions and air quality modelling M. Guevara et al. 10.1016/j.atmosenv.2014.10.029
- 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
- Improving Air Pollution Modelling in Complex Terrain with a Coupled WRF–LOTOS–EUROS Approach: A Case Study in Aburrá Valley, Colombia J. Hinestroza-Ramirez et al. 10.3390/atmos14040738
- Estimating Hourly Nitrogen Oxide Emissions over East Asia from Geostationary Satellite Measurements T. Xu et al. 10.1021/acs.estlett.3c00467
- Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis A. Datta et al. 10.1214/16-AOAS931
- Source attribution of nitrogen oxides across Germany: Comparing the labelling approach and brute force technique with LOTOS-EUROS M. Thürkow et al. 10.1016/j.atmosenv.2022.119412
- The effect of accounting for public holidays on the skills of the atmospheric composition model SILAM v.5.7 Y. Fatahi et al. 10.5194/gmd-14-7459-2021
- Transport emission models: A bibliometric and content analysis . Huma Rauf et al. 10.31580/jpvai.v5i2.2530
- 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 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
- Performance of European chemistry transport models as function of horizontal resolution M. Schaap et al. 10.1016/j.atmosenv.2015.04.003
- 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
- Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model A. Manders et al. 10.5194/gmd-10-4145-2017
- Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley – an integrated approach combining high-resolution dispersion modelling and micro-aethalometers G. Veratti et al. 10.5194/acp-24-10475-2024
- 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
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