Theoretically, what has been done during research has concerned the issue of air pollution in relation to vehicular traffic. Air pollution and related climate change have become key issues at national and international level, leading to the enactment of supranational laws and regulations. According to numerous studies and publications, such as the "White Paper" published by the European Commission, the main role of transport in improving air quality is clear.
It is clear from these considerations that forecasting tools are needed to provide designers and planners with the most realistic and reliable forecasting framework possible, in order to allow a correct management of the territory in key of improvement of the quality of the air.
The research was structured based on a preliminary analysis of the current available forecasting tools, which can be divided into two macro-families: static models and dynamic models.
The first category of models estimates emissions related to average parameters such as average speed; the second category of models correlates emissions to instantaneous parameters such as instantaneous speeds and acceleration. In the last years the increase of the traffics has significantly changed the real conditions of flow producing a strong increase of the interferences. This strongly affects driving styles and the use of static emission models, under certain conditions, can therefore lead to significant underestimations.
This aspect is all the greater if we consider the extra urban or urban areas where the variations of speed and the phenomena of stop&go prevent to use the parameter of the medium speed as representative of the phenomenon emissive In such cases the use of dynamic models allows a greater precision in the correlation of the emissive phenomenon, correlating the emissions directly to the operation of the vehicle in the real driving conditions. However, this approach requires a large amount of input data (such as video recordings and/or remote sensing).
In order to overcome the aforementioned critical issues, the research carried out in the doctoral course led to the definition of a new methodology of emission analysis with the aim of correlating emission factors to the main design variables such as traffic flows and geometries, through the use of an integrated simulation system.
The methodology allows to take into account the influence of the driving behavior of users in the different driving conditions, to vary the above-mentioned design parameters, through the use of the driving simulator in virtual reality. The methodology envisages using simulator output as the input of a specific dynamic emission estimation model.