Title
A high-order model for accurately simulating the size distribution of ultrafine particles in a traffic tunnel A high-order model for accurately simulating the size distribution of ultrafine particles in a traffic tunnel
Author
Faculty/Department
Faculty of Sciences. Bioscience Engineering
Publication type
article
Publication
Oxford ,
Subject
Physics
Chemistry
Biology
Source (journal)
Atmospheric environment : an international journal. - Oxford, 1994, currens
Volume/pages
59(2012) , p. 415-425
ISSN
1352-2310
ISI
000309081100047
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
We present a computational model for simulating the dispersion of traffic emitted particulate matter inside a road tunnel, with an emphasis on the number concentration of ultrafine particles (UFP). The model primarily calculates the size distribution of the particle number concentration at each location inside the tunnel. The proposed model differs from existing models in the sense that it uses a continuous representation of the size distribution based upon the high-order finite element method and that it solves the governing equations using the state-of-the-art discontinuous Galerkin method. Next to the traditional transport processes, the model also implements the most important aerosol transformation processes such as coagulation, condensation and dry deposition. It is shown that based upon parametrisations found in literature, the process of condensation in a traffic tunnel cannot properly be modelled. Therefore, we present a correction factor that allows for a better parametrisation. The adequate performance of the model is demonstrated by both a verification study and a validation study. For the verification we show that the discretisation error converges consistently while for the validation we compare the modelled results with a suitable set of data from a UFP measurement campaign in a Taiwanese traffic tunnel. The model is shown to correctly simulate the observed behaviour and by applying a statistical model evaluation we demonstrate that the proposed model meets widely accepted air quality model acceptance criteria. (C) 2012 Elsevier Ltd. All rights reserved.
E-info
https://repository.uantwerpen.be/docman/iruaauth/f68319/1a32762.pdf
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