Open AccessEnhanced air quality modelling through AUSTAL2000 model in Milan urban area
Author(s) -
Nicola Pepe,
Guido Pirovano,
Alessandra Balzarini,
A. Toppetti,
G. M. Riva,
Giovanni Lonati
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/296/1/012012
Subject(s) - air quality index , spatialization , lagrangian , environmental science , urban area , meteorology , air pollution , atmospheric dispersion modeling , geography , physics , chemistry , economy , organic chemistry , sociology , anthropology , economics , mathematical physics
Atmospheric dispersion models are a useful tools to assess air quality and emission source contributions in urban areas. Eulerian chemical and transport models (CTMs) can assess the regional background, that is the baseline level in the region of the city, and the urban background, that is the increment of concentration due to the emissions of the city, but they are not able to properly assess the very local contribution of emission sources at pollution hotspots within the city, because of their relatively large grid step. For the assessment of local sources’ contribution, Lagrangian dispersion models can be profitably used, especially when high spatial resolution modelling is required. Actually, Lagrangian models rely on a more realistic spatialization of urban emissions, unevenly distributed because of the road network layout (for traffic emissions) and of the built environment structure (for space heating emissions); additionally, Lagrangian models also account for wind field modifications induced by buildings. In this work, air quality modelling results for fine particles (PM2.5) in the city centre of Milan obtained by means of the AUSTAL2000 Lagrangian model are compared with those of CAMx Eulerian model. Model simulations where performed for a 1.7x1.7 km 2 area in Milan and focused on three receptor points selected in order to represent sites with both different features in terms of the surrounding built environment and different exposure to the local emission sources. Namely, the receptors correspond to a green area, to a residential and shopping area near Milan main square, and to a congested crossroad on the inner ring road of the city centre. Comparison results show that the outcome of the Eulerian model at the local scale is only representative of a background level, similar to Lagrangian model’s outcome for the green area receptor, but fails to reproduce concentration gradients and hot-spots, driven by local sources’ emissions.