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This paper illustrates the early results of ongoing research developing novel methods to analyse and simulate the relationship between trasport-related air pollutant concentrations and easily accessible explanatory variables. The final scope is to integrate the new models in traditional traffic management support systems for a sustainable mobility of road vehicles in urban areas.This first stage concerns the relationship between the hourly mean concentration of nitrogen dioxide (NO2) and explanatory factors reflecting the NO2 mean level one hour back, along with traffic and weather conditions. Particular attention is given to the prediction of pollution peaks, defined as exceedances of normative concentration limits. Two model frameworks are explored: the Artificial Neural Network approach and the ARIMAX model. Furthermore, the benefit of a synergic use of both models for air quality forecasting is investigated.The analysis of findings points out that the prediction of extreme concentrations is best performed by integrating the two models into an ensemble. The neural network is outperformed by the ARIMAX model in foreseeing peaks, but gives a more realistic representation of the concentration's dependency upon wind characteristics. So, the Neural Network can be exploited to highlight the involved functional forms and improve the ARIMAX model specification. In the end, the study shows that the ability to forecast exceedances of legal pollution limits can be enhanced by requiring traffic management actions when the predicted concentration exceeds a lower threshold than the normative one

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a b s t r a c tDuring 2012 the Italian passenger market has experienced the entry of a new operator, Nuovo Trasporto Viaggiatori (NTV) on the high speed rail (HSR) market segment, in competition with the incumbent Trenitalia. The Italian market is the first and most extensive case in Europe where two railway companies compete for HSR services on open access basis. In this paper we empirically explore the competitive effects of the newcomer's entry in the passenger market tackling two issues. First, we study price and capacity effects of the stemming intra-modal competition. Second, we measure the impact of inter-modal competition by HSR on airline pricing behaviour. The results show that the two railway companies engage in strategic pricing, although to a different degree on different routes and that capacity and frequency are strategic variables. We also find that airlines significantly reduce fares when flights are in direct competition with HSR services.

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