Articles | Volume 13, issue 4
https://doi.org/10.5194/gmd-13-1787-2020
© 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-13-1787-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
03 Apr 2020
Model evaluation paper |
| 03 Apr 2020
| 03 Apr 2020
Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions
Matthieu Pommier
CORRESPONDING AUTHOR
Norwegian Meteorological Institute, Oslo, Norway
Hilde Fagerli
Norwegian Meteorological Institute, Oslo, Norway
Michael Schulz
Norwegian Meteorological Institute, Oslo, Norway
Alvaro Valdebenito
Norwegian Meteorological Institute, Oslo, Norway
Richard Kranenburg
TNO, P.O. Box 80015, 3508TA Utrecht, the Netherlands
Martijn Schaap
TNO, P.O. Box 80015, 3508TA Utrecht, the Netherlands
FUB – Free University Berlin, Institut für Meteorologie,
Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
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Cited
16 citations as recorded by crossref.
- 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
- Why is the city's responsibility for its air pollution often underestimated? A focus on PM<sub>2.5</sub> P. Thunis et al. 10.5194/acp-21-18195-2021
- A new assessment of global and regional budgets, fluxes, and lifetimes of atmospheric reactive N and S gases and aerosols Y. Ge et al. 10.5194/acp-22-8343-2022
- Source attribution of particulate matter in Berlin J. Pültz et al. 10.1016/j.atmosenv.2022.119416
- Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting M. Pang et al. 10.5194/gmd-17-8223-2024
- Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e W. van Caspel et al. 10.5194/gmd-16-7433-2023
- Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution M. Pommier 10.5194/gmd-14-4143-2021
- Global sensitivities of reactive N and S gas and particle concentrations and deposition to precursor emissions reductions Y. Ge et al. 10.5194/acp-23-6083-2023
- Ultrafine particle emission from floor cleaning products L. Stabile et al. 10.1111/ina.12713
- Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements P. Broomandi et al. 10.1016/j.envpol.2023.121232
- Short-term exposure to some heavy metals carried with PM10 and cardiovascular system biomarkers during dust storm A. Badeenezhad et al. 10.1038/s41598-023-31978-x
- Use of the Copernicus Atmosphere Monitoring Service policy products to evaluate the contribution of EU cities to their pollution E. Pisoni et al. 10.1016/j.aeaoa.2022.100194
- Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe J. Putaud et al. 10.5194/acp-23-10145-2023
- Modelling benzo(a)pyrene concentrations for different meteorological conditions – Analysis of lung cancer cases and associated economic costs P. Porwisiak et al. 10.1016/j.envint.2023.107863
- Source apportionment of air pollution in European urban areas: Lessons from the ClairCity project S. Coelho et al. 10.1016/j.jenvman.2022.115899
- Application of Positive Matrix Factorization Receptor Model for Source Identification of PM10 in the City of Sofia, Bulgaria E. Hristova et al. 10.3390/atmos11090890
16 citations as recorded by crossref.
- 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
- Why is the city's responsibility for its air pollution often underestimated? A focus on PM<sub>2.5</sub> P. Thunis et al. 10.5194/acp-21-18195-2021
- A new assessment of global and regional budgets, fluxes, and lifetimes of atmospheric reactive N and S gases and aerosols Y. Ge et al. 10.5194/acp-22-8343-2022
- Source attribution of particulate matter in Berlin J. Pültz et al. 10.1016/j.atmosenv.2022.119416
- Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting M. Pang et al. 10.5194/gmd-17-8223-2024
- Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e W. van Caspel et al. 10.5194/gmd-16-7433-2023
- Prediction of source contributions to urban background PM<sub>10</sub> concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution M. Pommier 10.5194/gmd-14-4143-2021
- Global sensitivities of reactive N and S gas and particle concentrations and deposition to precursor emissions reductions Y. Ge et al. 10.5194/acp-23-6083-2023
- Ultrafine particle emission from floor cleaning products L. Stabile et al. 10.1111/ina.12713
- Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements P. Broomandi et al. 10.1016/j.envpol.2023.121232
- Short-term exposure to some heavy metals carried with PM10 and cardiovascular system biomarkers during dust storm A. Badeenezhad et al. 10.1038/s41598-023-31978-x
- Use of the Copernicus Atmosphere Monitoring Service policy products to evaluate the contribution of EU cities to their pollution E. Pisoni et al. 10.1016/j.aeaoa.2022.100194
- Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe J. Putaud et al. 10.5194/acp-23-10145-2023
- Modelling benzo(a)pyrene concentrations for different meteorological conditions – Analysis of lung cancer cases and associated economic costs P. Porwisiak et al. 10.1016/j.envint.2023.107863
- Source apportionment of air pollution in European urban areas: Lessons from the ClairCity project S. Coelho et al. 10.1016/j.jenvman.2022.115899
- Application of Positive Matrix Factorization Receptor Model for Source Identification of PM10 in the City of Sofia, Bulgaria E. Hristova et al. 10.3390/atmos11090890
Latest update: 14 Dec 2024
Short summary
The EMEP and LOTOS-EUROS models comprise the operational source contribution prediction system for the European cities within the Copernicus Atmosphere Monitoring Service (CAMS). This study presents a first evaluation of this system, with hourly resolution, by focusing on one PM10 episode in December 2016, dominated by the influence of domestic emissions. It shows that the system provides valuable information on the composition and contributions of different countries to PM10.
The EMEP and LOTOS-EUROS models comprise the operational source contribution prediction system...
