AQSensor 2

Monitoring air quality and environmental conditions is an important activity. Many people, especially in cities, are exposed to higher levels of air pollutants than the limit values according to EU and Swedish legislation. Road traffic emissions are the dominant source of air pollutants in urban environments such as NOx, CO, VOC, and PM. Traffic pollutants are of health concern. According to WHO, air pollution is one of the major causes of mortality worldwide. Moreover, traffic generated greenhouse chemicals, such as CO2 and black carbon (BC), are also directly related to global climate changes.

Strategies to mitigate the environmental effects of traffic include measures to promote public transport, walking and biking, policies for vehicle and fuel taxation, congestion pricing, mobility credits (for example including freight transport actors) and eco-routing, as well as active traffic management and predictive traffic control. The time scale over which these approaches are applied varies, some planned far ahead of time, while others are exercised in real time based on current conditions. In all cases though, successful and effective implementation of such policies and strategies requires accurate measurement of traffic conditions and their environmental impacts.

However, existing models, relating traffic conditions to road-side emissions, depend on a number of parameters that are rarely calibrated, based on default values obtained under conditions that may not be representative of actual conditions. Part of the limitation is also that air pollutants are monitored with data collected from few stations at roadside, and such data has not been applied in transport management and traffic environmentanalysis.

The fast development and increasing availability of air quality (AQ) sensors have made AQ data a promising information source for direct measurement of traffic-induced emissions and therefore suitable for development of sustainable traffic management measures. This project aims to:

1. install an IoT sensor network near Swedish motorways to collect data on and monitor continuously important, traffic generated, air pollutants such as CO, NOx, noise etc; 
2. analyse such data with existing traffic measurements (e.g. MCS data) near highways for emission prediction
3. integrate traffic and AQ models in the analysis of traffic-induced emissions;
4. develop traffic control algorithms with consideration of mitigating traffic emissions using real-time feedback information on air quality of roadside.