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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-90
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-90
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: methods for assessment of models 25 May 2020

Submitted as: methods for assessment of models | 25 May 2020

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A revised version of this preprint is currently under review for the journal GMD.

Prioritising the sources of pollution in European cities: do air quality modelling applications provide consistent responses?

Bart Degraeuwe, Enrico Pisoni, and Philippe Thunis Bart Degraeuwe et al.
  • European Commission, Joint Research Centre (JRC), Ispra, Italy

Abstract. To take decisions on how to improve air quality, it is useful to perform a source allocation study that identifies the main sources of pollution for the area of interest. Often source allocation is implemented with a Chemical Transport Model (CTM) but unfortunately, even if accurate, this technique is time consuming and complex. Comparing the results of different CTMs to assess the uncertainty on the results is even more difficult. In this work we compare the source allocation on 150 major cities in Europe based on the results of two CTMs (CHIMERE and EMEP), approximated through the SHERPA (Screening for High Emission Reduction Potential on Air) approach. Even though the two CTMs use different input data and configurations, in most cases the source allocations with the SHERPA simplified models give similar results. But there are also cases where results are contradictory.

Bart Degraeuwe et al.

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Bart Degraeuwe et al.

Bart Degraeuwe et al.

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Latest update: 28 Sep 2020
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Short summary
To take decisions on how to improve air quality, it is useful to identify the main sources of pollution for an area of interest. Often these sources of pollution are identified with complex models that, even if accurate, are time consuming and complex. In this work we use another approach, simplified models, to accomplish the same task. The results, computed with two different set of simplified models, show the main sources of pollution for selected cities, and the associated uncertainties.
To take decisions on how to improve air quality, it is useful to identify the main sources of...
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