Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black
carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC
and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are
designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of
traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line
recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to
reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented
and evaluated in two pilot cities, Graz and Glasgow.
Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale
traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for
several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses all these model
simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously
monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC.