Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-6303-2020
© 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-13-6303-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
11 Dec 2020
Model description paper |
| 11 Dec 2020
| 11 Dec 2020
Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model
Bruce Rolstad Denby
CORRESPONDING AUTHOR
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Michael Gauss
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Peter Wind
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Department of Chemistry, UiT – The Arctic University of Norway,
9037 Tromsø, Norway
Qing Mu
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Eivind Grøtting Wærsted
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Hilde Fagerli
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Alvaro Valdebenito
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
Heiko Klein
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313,
Oslo, Norway
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Cited
18 citations as recorded by crossref.
- Quantification of temperature dependence of NO emissions from road traffic in Norway using air quality modelling and monitoring data E. Wærsted et al. 10.1016/j.aeaoa.2022.100160
- Assessment of the sensitivity of model responses to urban emission changes in support of emission reduction strategies B. Bessagnet et al. 10.1007/s11869-023-01469-z
- A source apportionment and air quality planning methodology for NO2 pollution from traffic and other sources B. Degraeuwe et al. 10.1016/j.envsoft.2024.106032
- To what extent the traffic restriction policies applied in Barcelona city can improve its air quality? D. Rodriguez-Rey et al. 10.1016/j.scitotenv.2021.150743
- Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements Y. Ge et al. 10.5194/gmd-14-7021-2021
- Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting A. Murad et al. 10.3390/s21238009
- Downscaling of air pollutants in Europe using uEMEP_v6 Q. Mu et al. 10.5194/gmd-15-449-2022
- An Online Downscaling Method to Simulate High Resolution Atmospheric Concentrations of Pesticides with the 3D Chemistry-Transport Model CHIMERE: Application and Evaluation F. Couvidat et al. 10.1016/j.atmosenv.2023.120092
- Revised EU and WHO air quality thresholds: Where does Europe stand? A. Beloconi & P. Vounatsou 10.1016/j.atmosenv.2023.120110
- Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India G. Govardhan et al. 10.5194/gmd-17-2617-2024
- Estimates of population exposure to atmospheric pollution and health-related externalities in a real city: The impact of spatial resolution on the accuracy of results J. Santiago et al. 10.1016/j.scitotenv.2021.152062
- A simple and fast method to downscale chemistry transport model output fields from the regional to the urban/district scale B. Bessagnet et al. 10.1016/j.envsoft.2023.105692
- Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0 A. Criado et al. 10.5194/gmd-16-2193-2023
- Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems P. Schneider et al. 10.3390/atmos14030540
- The UrbEm Hybrid Method to Derive High-Resolution Emissions for City-Scale Air Quality Modeling M. Ramacher et al. 10.3390/atmos12111404
- An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation L. Johansson et al. 10.1016/j.envsoft.2022.105460
- Effect of vehicle fleet composition and mobility on outdoor population exposure: A street resolution analysis in Paris L. Lugon et al. 10.1016/j.apr.2022.101365
- Analysing the environmental impact of IMO sulphur regulation 2020, annex VI, MARPOL A. Singh & S. Shanthakumar 10.56398/ajacieda.00072
17 citations as recorded by crossref.
- Quantification of temperature dependence of NO emissions from road traffic in Norway using air quality modelling and monitoring data E. Wærsted et al. 10.1016/j.aeaoa.2022.100160
- Assessment of the sensitivity of model responses to urban emission changes in support of emission reduction strategies B. Bessagnet et al. 10.1007/s11869-023-01469-z
- A source apportionment and air quality planning methodology for NO2 pollution from traffic and other sources B. Degraeuwe et al. 10.1016/j.envsoft.2024.106032
- To what extent the traffic restriction policies applied in Barcelona city can improve its air quality? D. Rodriguez-Rey et al. 10.1016/j.scitotenv.2021.150743
- Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements Y. Ge et al. 10.5194/gmd-14-7021-2021
- Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting A. Murad et al. 10.3390/s21238009
- Downscaling of air pollutants in Europe using uEMEP_v6 Q. Mu et al. 10.5194/gmd-15-449-2022
- An Online Downscaling Method to Simulate High Resolution Atmospheric Concentrations of Pesticides with the 3D Chemistry-Transport Model CHIMERE: Application and Evaluation F. Couvidat et al. 10.1016/j.atmosenv.2023.120092
- Revised EU and WHO air quality thresholds: Where does Europe stand? A. Beloconi & P. Vounatsou 10.1016/j.atmosenv.2023.120110
- Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India G. Govardhan et al. 10.5194/gmd-17-2617-2024
- Estimates of population exposure to atmospheric pollution and health-related externalities in a real city: The impact of spatial resolution on the accuracy of results J. Santiago et al. 10.1016/j.scitotenv.2021.152062
- A simple and fast method to downscale chemistry transport model output fields from the regional to the urban/district scale B. Bessagnet et al. 10.1016/j.envsoft.2023.105692
- Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0 A. Criado et al. 10.5194/gmd-16-2193-2023
- Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems P. Schneider et al. 10.3390/atmos14030540
- The UrbEm Hybrid Method to Derive High-Resolution Emissions for City-Scale Air Quality Modeling M. Ramacher et al. 10.3390/atmos12111404
- An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation L. Johansson et al. 10.1016/j.envsoft.2022.105460
- Effect of vehicle fleet composition and mobility on outdoor population exposure: A street resolution analysis in Paris L. Lugon et al. 10.1016/j.apr.2022.101365
1 citations as recorded by crossref.
Latest update: 24 Apr 2024
Short summary
Air pollution is both a local and a global problem. Since measurements cannot be made everywhere, mathematical models are used to calculate air quality over cities or countries. Modelling over countries limits the level of detail of the models. For countries, the level of detail is only a few kilometres, so air quality at kerb sides is not properly represented. The uEMEP model is used together with the regional air quality model EMEP MSC-W to model details down to kerb side for all of Norway.
Air pollution is both a local and a global problem. Since measurements cannot be made...
