Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp

F. Martín (1) , S. Janssen (2) , V. Rodrigues (3) , J. Sousa (2) , J.L. Santiago (1) , E. Rivas (1) , J. Stocker (4) , R. Jackson (4) , F. Russo (5) , M.G. Villani (5) , G. Tinarelli (6) , D. Barbero (6) , R. San José , J.L. Pérez-Camanyo , G. Sousa Santos (7) , J. Bartzis (8) , I. Sakellaris (8) , Z. Horváth (9) , L. Környei (9) , B. Liszkai (9) , Á. Kovács (9) , X. Jurado (10) , N. Reiminger (11, 10) , P. Thunis (12) , C. Cuvelier (12)

1 CIEMAT - Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
2 VITO - Flemish Institute for Technological Research
3 CESAM - Centre for Environmental and Marine Studies [Aveiro]
4 Cambridge Environmental Research Consultants
5 ENEA - Italian National agency for new technologies, Energy and sustainable economic development [Frascati]
6 ARIANET Srl
7 NILU - Norwegian Institute for Air Research
8 UoWM - University of Western Macedonia [Kozani]
9 Széchenyi István University
10 AIR & D [Illkirch-Graffenstaden]
11 ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
12 JRC - European Commission - Joint Research Centre [Ispra]

In the framework of the Forum for Air Quality Modelling in Europe (FAIRMODE), a modelling intercomparison exercise for computing NO2 long-term average concentrations in urban districts with a very high spatial resolution was carried out. This exercise was undertaken for a district of Antwerp (Belgium). Air quality data includes data recorded in air quality monitoring stations and 73 passive samplers deployed during one-month period in 2016. The modelling domain was 800 × 800 m2. Nine modelling teams participated in this exercise providing results from fifteen different modelling applications based on different kinds of model approaches (CFD – Computational Fluid Dynamics-, Lagrangian, Gaussian, and Artificial Intelligence). Some approaches consisted of models running the complete one-month period on an hourly basis, but most others used a scenario approach, which relies on simulations of scenarios representative of wind conditions combined with post-processing to retrieve a one-month average of NO2 concentrations. The objective of this study is to evaluate what type of modelling system is better suited to get a good estimate of long-term averages in complex urban districts. This is very important for air quality assessment under the European ambient air quality directives. The time evolution of NO2 hourly concentrations during a day of relative high pollution was rather well estimated by all models. Relative to high resolution spatial distribution of one-month NO2 averaged concentrations, Gaussian models were not able to give detailed information, unless they include building data and street-canyon parameterizations. The models that account for complex urban geometries (i.e. CFD, Lagrangian, and AI models) appear to provide better estimates of the spatial distribution of one-month NO2 averages concentrations in the urban canopy. Approaches based on steady CFD-RANS (Reynolds Averaged Navier Stokes) model simulations of meteorological scenarios seem to provide good results with similar quality to those obtained with an unsteady one-month period CFD-RANS simulations.

Mots clés: Air pollution; Model intercomparison; Microscale modelling; Urban area; NO2; Long-term concentration

Domaines: Modélisation et simulation; Biodiversité et Ecologie; Ingénierie de l'environnement

F. Martín, S. Janssen, V. Rodrigues, J. Sousa, J.L. Santiago, et al.. Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp. Science of the Total Environment, 2024, 925, pp.171761. ⟨10.1016/j.scitotenv.2024.171761⟩. ⟨hal-04513628⟩