TRAFAIR (Understanding Traffic Flows to Improve Air Quality)

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Laura Po (UNIMORE, Italy)
Raquel Trillo-Lado (DisCo-I3A, Unizar)

356.310 € (Unizar)


The Trafair project brings together 10 partners from two European countries (Italy and Spain) to develop innovative and sustainable services combining air quality, weather conditions, and traffic flows data to produce new information for the benefit of citizens and government decision-makers.


Air pollution causes 400,000 deaths per year, making it first environmental cause of premature death in Europe. Among the main sources of air pollution in Europe, there are road traffic, domestic heating, and industrial combustion. Nowadays, the situation is particularly critical in some member states of Europe. In February 2017, the European Commission warned five countries, among which Spain and Italy, of continued air pollution breaches. These countries fail to address repeated breaches of air pollution limits for nitrogen dioxide (NO2) whose most emissions result from road traffic. The European Commission urged these Member States to take action to ensure good air quality and safeguard public health. In this context, public administrations and citizens suffer from the lack of comprehensive and fast tools to estimate the level of pollution on an urban scale resulting from varying traffic flow conditions that would allow optimizing control strategies and increase air quality awareness.


TRAFAIR raises awareness among citizens and public administrations about the air quality within an urban environment and the pollution caused by traffic. The project aims at monitoring air quality by using sensors in six cities and making air quality predictions thanks to simulation models. The two main goals of the project are:

1) Monitoring urban air quality by using sensors in 6 European cities: Zaragoza (600,000 inhabitants), Florence (382,000), Modena (185,000), Livorno (160,000), Santiago de Compostela (95,000) and Pisa (90,000);

2) Making urban air quality predictions thanks to simulation models based on weather forecast and traffic flows.