High-resolution air quality simulations are often performed using different nested domains
and resolutions. In this study, the variability of nitrogen dioxide (NO2) concentrations estimated from
two nested domains focused on Portugal (D2 and D3), with 5 and 1 km horizontal grid resolutions,
respectively, was investigated by applying the WRF-Chem model for the year 2015. The main goal
and innovative aspect of this study is the simulation of a whole year with high resolutions to analyse
the spatial variability under the simulation grids in conjunction with detailed land cover (LC) data
specifically processed for these high-resolution domains. The model evaluation was focused on
Portuguese air quality monitoring stations taking into consideration the station typology. As main
results, it should be noted that (i) D3 urban LC categories enhanced pollution hotspots; (ii) generally,
modelled NO2 was underestimated, except for rural stations; (iii) differences between D2 and D3
estimates were small; (iv) higher resolution did not impact model performance; and (v) hourly
D2 estimates presented an acceptable quality level for policy support. These modelled values are
based on a detailed LC classification (100 m horizontal resolution) and coarse spatial resolution
(approximately 10 km) emission inventory, the latter suitable for portraying background air pollution
problems. Thus, if the goal is to characterise urban/local-scale pollution patterns, the use of high
grid resolution could be advantageous, as long as the input data are properly represented.
The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020), SusTEC (LA/P/0007/2020) and CESAM (UIDP/50017/2020 + UIDB/50017/2020 + LA/P/0094/2020), and for the contract granted to Joana Ferreira (2020.00622.CEECIND). Thanks are also due for financial support to OleaChain project “Skills for sustainability and innovation in the value chain of traditional olive groves in the Northern Interior of Portugal” (NORTE-06-3559-FSE-000188).
