The project aims to realize a method, system and tools for adaptively influencing traffic in real-time to reduce CO2- and black carbon (BC) emissions caused by road transport in urban and inter-urban areas. BC is suspected to be the second main contributor-next to CO2-to global warming. The inter-relationships between traffic flow and CO2- and BC emissions will be considered. In particular a model linking traffic flows to emission levels will be established on the basis of existing and new simulation methods and tools.The main goal of the project is the development, integration and evaluation of a real-time decision support system for adaptive traffic control and management. Real-time traffic information will be delivered by existing sensors and by a novel technology vision sensor, air quality sensors and additional data sources (e.g. weather conditions) enrich the data base to provide all relevant information in a unified fashion. Based on a data base of predefined traffic scenarios traffic control measures will be dynamically imposed. The impact of the measures on the overall CO2 - and BC emissions will be accounted for in the decision support system and will be assessed in the evaluation. Furthermore, the effects of reduced traffic on urban air pollutants (relevant for human health), with a special focus on BC as a pollutant, will also be considered, thus allowing to evaluate the value added of climate protection measures for the urban population. The system will be implemented and tested in two EU cities (Graz,AT and Glasgow,UK).This project brings together two important communities. The traffic community is represented by AIT, IBM, VITO, Österreichisches Forschungs- und Prüfzentrum Arsenal (ÖFPZ) and EBE-Solutions Austria with long standing experience in traffic monitoring, simulation, analysis and management. The air quality community is represented by Air Monitors UK, ETS, London Imperial College and again by VITO.