The main objective of this research is to assess the effects of the implementation of mobility policies on air quality in an urban area. To improve the estimation of urban air quality, it is necessary to use modelling tools capable of providing accurate and detailed answers at the spatial scale of interest. Three improvements to the modelling system are presented in this report.

The first concerns the activities carried out within the European LIFE-REMY project in particular the results related to the estimation of resuspension emissions from road traffic, which is one of the greatest sources of uncertainty in the assessment of road transport role on air quality. Next, two preliminary activities are presented concerning the introduction of new models in the modelling set-up: the first dedicated to the accurate simulation of urban traffic flows and the second aimed at improving the high-resolution modelling of pollutant dispersion in urban areas.

Scenario analysis to support sustainable mobility policy evaluation continues, with the simulation of a scenario involving the establishment of a Zero Emission Zone in Milan in 2030. In order to correctly simulate the concentrations in a future scenario, it is also necessary to project the emissions of the base year to scenario year.

Changes in road transport vehicle fleet leads to a significant reduction in emissions compared to the 2017 base case (84% NOx, 28% PM2.5). Added to these reductions is the effect of the ZEZ, which contributes to a further reduction in traffic emissions, albeit to a smaller extent due to the limited size of the ZEZ (2.2% NOx, 0.9% PM2.5).

The contribution of the ZEZ is in addition to the significant reduction in concentrations estimated following the emission reductions planned for 2030, introduces a further slight localised improvement in the city centre. Finally, in order to extend the estimation of the impacts of air pollution on the population to the local scale, a methodology capable of considering the actual movements of people (dynamic exposure) was introduced.

This method improves the estimation of exposure compared to the traditional static approach.

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