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

• DOI: 10.1016/j.scitotenv.2024.171761
• Publication Date: 2024-03-16T06:51:42Z
• Authors: F. Martín; S. Janssen; V. Rodrigues; J. Sousa; J.L. Santiago; E. Rivas; J. Stocker; R. Jackson; F. Russo; M.G. Villani; G. Tinarelli; D. Barbero; R. San José; J.L. Pérez-Camanyo; G. Sousa Santos; J. Bartzis; I. Sakellaris; Z. Horváth; L. Környei; B. Liszkai; Á. Kovács; X. Jurado; N. Reiminger; P. Thunis; C. Cuvelier
• Keywords: Microscale chemistry; Temporal resolution; CMAQ

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