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Atmosphere 2018, 9(1), 8;

Source Apportionment and Data Assimilation in Urban Air Quality Modelling for NO2: The Lyon Case Study

Laboratoire de Mécanique des Fluides et d’Acoustique, UMR CNRS 5509 University of Lyon, Ecole Centrale de Lyon, INSA Lyon, Université Claude Bernard Lyon I, 36, avenue Guy de Collongue, 69134 Ecully, France
Author to whom correspondence should be addressed.
Received: 7 September 2017 / Revised: 17 December 2017 / Accepted: 18 December 2017 / Published: 1 January 2018
(This article belongs to the Special Issue Recent Advances in Urban Ventilation Assessment and Flow Modelling)
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Developing effective strategies for reducing the atmospheric pollutant concentrations below regulatory threshold levels requires identifying the main origins/sources of air pollution. This can be achieved by implementing so called source apportionment methods in atmospheric dispersion models. This study presents the results of a source apportionment module implemented in the SIRANE urban air-quality model. This module uses the tagged species approach and includes two methods, named SA-NO and SA-NOX, in order to evaluate the sources’ contributions to the NO 2 concentrations in air. We also present results of a data assimilation method, named SALS, that uses the source apportionment estimates to improve the accuracy of the SIRANE model results. The source apportionment module and the assimilation method have been tested on a real case study (the urban agglomeration of Lyon, France, for the year 2008) focusing on the NO 2 emissions and concentrations. Results of the source apportionment with the SA-NO and SA-NOX models are similar. Both models show that traffic is the main cause of NO 2 air pollution in the studied area. Results of the SALS data assimilation method highlights its ability in improving the predictions of an urban atmospheric models. View Full-Text
Keywords: source apportionment; data assimilation; urban air quality modelling source apportionment; data assimilation; urban air quality modelling

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Nguyen, C.V.; Soulhac, L.; Salizzoni, P. Source Apportionment and Data Assimilation in Urban Air Quality Modelling for NO2: The Lyon Case Study. Atmosphere 2018, 9, 8.

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