Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model
<p>A description of the new air quality downscaling model – the urban EMEP (uEMEP) and its combination with the EMEP MSC-W model (European Monitoring and Evaluation Programme Meteorological Synthesising Centre West) – is presented. uEMEP is based on well-known Gaussian modelling principles. T...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Sprog: | English |
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Copernicus Publications
2020-12-01
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| Serier: | Geoscientific Model Development |
| Online adgang: | https://gmd.copernicus.org/articles/13/6303/2020/gmd-13-6303-2020.pdf |
| _version_ | 1830095881972482048 |
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| author | B. R. Denby M. Gauss P. Wind P. Wind Q. Mu E. Grøtting Wærsted H. Fagerli A. Valdebenito H. Klein |
| author_facet | B. R. Denby M. Gauss P. Wind P. Wind Q. Mu E. Grøtting Wærsted H. Fagerli A. Valdebenito H. Klein |
| author_sort | B. R. Denby |
| collection | DOAJ |
| description | <p>A description of the new air quality downscaling model –
the urban EMEP (uEMEP) and its combination with the EMEP MSC-W model (European Monitoring and Evaluation Programme Meteorological Synthesising Centre West) – is presented. uEMEP is based on well-known Gaussian modelling principles. The
uniqueness of the system is in its combination with the EMEP MSC-W model and
the “local fraction” calculation contained within it. This allows the uEMEP
model to be imbedded in the EMEP MSC-W model and downscaling can be carried
out anywhere within the EMEP model domain, without any double counting of
emissions, if appropriate proxy data are available that describe the spatial
distribution of the emissions. This makes the model suitable for high-resolution
calculations, down to 50 m, over entire countries. An example
application, the Norwegian air quality forecasting and assessment system, is
described where the entire country is modelled at a resolution of between
250 and 50 m. The model is validated against all available monitoring data,
including traffic sites, in Norway. The results of the validation show good
results for NO<span class="inline-formula"><sub>2</sub></span>, which has the best known emissions, and moderately
good for PM<span class="inline-formula"><sub>10</sub></span> and PM<span class="inline-formula"><sub>2.5</sub></span>. In Norway, the largest contributor to PM,
even in cities, is long-range transport followed by road dust and domestic
heating emissions. These contributors to PM are more difficult to quantify
than NO<span class="inline-formula"><sub><i>x</i></sub></span> exhaust emission from traffic, which is the major contributor
to NO<span class="inline-formula"><sub>2</sub></span> concentrations. In addition to the validation results, a number
of verification and sensitivity results are summarised. One verification
showed that single annual mean calculations with a rotationally symmetric
dispersion kernel give very similar results to the average of an entire year
of hourly calculations, reducing the runtime for annual means by 4 orders
of magnitude. The uEMEP model, in combination with EMEP MSC-W model,
provides a new tool for assessing local-scale concentrations and exposure
over large regions in a consistent and homogenous way and is suitable for
large-scale policy applications.</p> |
| first_indexed | 2024-12-16T19:34:03Z |
| format | Article |
| id | doaj.art-54ea556cc1f7490f90d2bacf45f21ae4 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-16T19:34:03Z |
| publishDate | 2020-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-54ea556cc1f7490f90d2bacf45f21ae42022-12-21T22:19:18ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032020-12-01136303632310.5194/gmd-13-6303-2020Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport modelB. R. Denby0M. Gauss1P. Wind2P. Wind3Q. Mu4E. Grøtting Wærsted5H. Fagerli6A. Valdebenito7H. Klein8The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayDepartment of Chemistry, UiT – The Arctic University of Norway, 9037 Tromsø, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, NorwayThe Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, Norway<p>A description of the new air quality downscaling model – the urban EMEP (uEMEP) and its combination with the EMEP MSC-W model (European Monitoring and Evaluation Programme Meteorological Synthesising Centre West) – is presented. uEMEP is based on well-known Gaussian modelling principles. The uniqueness of the system is in its combination with the EMEP MSC-W model and the “local fraction” calculation contained within it. This allows the uEMEP model to be imbedded in the EMEP MSC-W model and downscaling can be carried out anywhere within the EMEP model domain, without any double counting of emissions, if appropriate proxy data are available that describe the spatial distribution of the emissions. This makes the model suitable for high-resolution calculations, down to 50 m, over entire countries. An example application, the Norwegian air quality forecasting and assessment system, is described where the entire country is modelled at a resolution of between 250 and 50 m. The model is validated against all available monitoring data, including traffic sites, in Norway. The results of the validation show good results for NO<span class="inline-formula"><sub>2</sub></span>, which has the best known emissions, and moderately good for PM<span class="inline-formula"><sub>10</sub></span> and PM<span class="inline-formula"><sub>2.5</sub></span>. In Norway, the largest contributor to PM, even in cities, is long-range transport followed by road dust and domestic heating emissions. These contributors to PM are more difficult to quantify than NO<span class="inline-formula"><sub><i>x</i></sub></span> exhaust emission from traffic, which is the major contributor to NO<span class="inline-formula"><sub>2</sub></span> concentrations. In addition to the validation results, a number of verification and sensitivity results are summarised. One verification showed that single annual mean calculations with a rotationally symmetric dispersion kernel give very similar results to the average of an entire year of hourly calculations, reducing the runtime for annual means by 4 orders of magnitude. The uEMEP model, in combination with EMEP MSC-W model, provides a new tool for assessing local-scale concentrations and exposure over large regions in a consistent and homogenous way and is suitable for large-scale policy applications.</p>https://gmd.copernicus.org/articles/13/6303/2020/gmd-13-6303-2020.pdf |
| spellingShingle | B. R. Denby M. Gauss P. Wind P. Wind Q. Mu E. Grøtting Wærsted H. Fagerli A. Valdebenito H. Klein Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model Geoscientific Model Development |
| title | Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model |
| title_full | Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model |
| title_fullStr | Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model |
| title_full_unstemmed | Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model |
| title_short | Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model |
| title_sort | description of the uemep v5 downscaling approach for the emep msc w chemistry transport model |
| url | https://gmd.copernicus.org/articles/13/6303/2020/gmd-13-6303-2020.pdf |
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