# Semantic Traffic Sensor Data:
## 3 Traffic Modelling in TRAFAIR
### Scope and Purpose of the TRAFAIR Project  
Pollution is the primary environmental cause of premature death in Europe. Thus, according to a European Union (EU) report published by the European Environmental Agency [41], poor air quality caused \(412,000\) premature deaths in Europe in 2016. Intending to improve air quality, the European Commission is carrying out several policies with their respective legislative measures. However, nowadays, the situation is still critical in some member states that cannot reach the goals fixed by Europe. Indeed, in February 2017, the European Commission warned five countries (Spain and Italy, among them) about continuous violations of rules established regarding atmospheric pollution. These countries are having difficulties in controlling the levels of \(NO_{2}\) emissions within the allowable ranges, that are mainly produced by the traffic of vehicles. Therefore, the European Commission requires its member states to perform actions to guarantee the quality of air and safeguard public health. In this context, public administrations and citizens lack a complete set of tools to allow the estimation of the level of pollution at an urban scale, which depends on the variable traffic conditions, which would lead to an optimization of the control strategies and an increase of the air quality awareness.  
Motivated by the problems mentioned above, the overall goal of the TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project [42; 43] is to develop a service that will allow citizens and municipalities to estimate and predict urban air quality in six cities in Europe. The prediction estimation, in particular, is produced by considering the 3-D shape of city buildings, meteorological conditions, and traffic flows. As part of the project, datasets representing urban air quality maps will be published in catalogs of data collected by the European Data Portal [2]. Besides, different use cases will be considered, including the development of mobile apps for final users. More specifically, the main goals are the following:  
1. The definition of a standard set of metadata, extending the ones adopted at the European level and defined by FAIRMODE [44], able to represent urban air quality maps [45].
2. The provision of real-time estimations of air pollution in a city on an urban scale. For this purpose, low-cost air quality sensors are deployed, combining their measures with measures provided by official air quality stations to build informative maps of the different levels of pollution in different urban areas.
3. The development of a service to predict the urban air quality based on meteorological prediction and traffic flow, using High-Performance Computing (HPC) technologies to estimate the dissemination of pollutants. A traffic flow model is used to simulate new circulation hypothesis (e.g., changes regarding the types of vehicles and their proportions in the float of vehicles in the city, increments in the number of low-emission vehicles used, the definition of areas with restricted circulation in a city, etc.) and their impact on the air quality.
4. The publication, in catalogs collected by the European Data Portal, of open datasets describing urban air quality maps of six European cities of diverse size where the service will be deployed: Zaragoza (Spain), with about 600,000 inhabitants, Florence (Italy), with about 382,000 inhabitants, Modena (Italy), with about 185,000 inhabitants, Livorno (Italy), with about 160,000 inhabitants, Santiago de Compostela (Spain), with about 95,000 inhabitants, and Pisa (Italy), with about 90,000 inhabitants.  
As mentioned previously, the transport sector is responsible for a large proportion of urban air pollution. Therefore, this paper focuses on traffic data and presents our data modeling, data integration, and data publication strategy followed for traffic data in the context of the TRAFAIR project.