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 these off-line 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.