To what extent is the description of streets important in estimating local air quality: a case study over Paris

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Modeling atmospheric composition at street level is challenging because pollutant concentrations within street canyons depend on both local emissions and the transport of polluted air masses from remote areas. Therefore, regional-scale modeling and local applications must be combined to provide accurate simulations of the atmospheric composition at street locations. In our study, we compare two strategies: (i) a subgrid-scale approach embedded in the chemistry–transport model (denoted Subgrid) and (ii) the street-network model MUNICH (Model of Urban Network of Intersecting Canyons and Highways). In both cases, the regional-scale chemistry–transport model CHIMERE provides the urban background concentrations, and the meteorological model Weather Research and Forecasting (WRF), coupled with CHIMERE, is used to provide meteorological fields. Simulation results for NO x , NO 2 , and PM 2.5 concentrations over the city of Paris from both modeling approaches are compared with in situ measurements from traffic air quality stations. At stations located in downtown areas, with low traffic emissions, the street-network model MUNICH exhibits superior performance compared to the Subgrid approach for NO x concentrations, while comparable results are obtained for NO 2 . However, significant discrepancies between the two methods are observed for all analyzed pollutants at stations heavily influenced by road traffic. These stations are typically located near highways, where the difference between the two approaches can reach 58 %. The ability of the Subgrid approach to estimate accurate emission data is limited, leading to potential underestimation or overestimation of gas and fine-particle concentrations based on the emission heterogeneity it handles. The performance of MUNICH appears to be highly sensitive to the friction velocity, a parameter influenced by the anthropogenic heat flux used in the WRF model. Street dimensions do contribute to the performance disparities observed between the two approaches, yet emissions remain the predominant factor.

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